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Microsoft Research Podcast on Smash Notes

Microsoft Research Podcast podcast.

December 28, 2019

An ongoing series of conversations bringing you right up to the cutting edge of Microsoft Research.



Episodes with Smash Notes

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.


Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

Updated on June 10

Dynamic random-access memory – or DRAM – is the most popular form of volatile computer memory in the world but it’s particularly susceptible to Rowhammer, an adversarial attack that can cause data loss and security exploits in everything from smart phones to the cloud.


Today, Dr. Stefan Saroiu, a Senior Principal Researcher in MSR’s Mobility and Networking group, explains why DRAM remains vulnerable to Rowhammer attacks today, even after several years of mitigation efforts, and then tells us how a new approach involving bespoke extensibility mechanisms for DRAM might finally hammer Rowhammer in the fight to keep data safe and secure.

Many computer science researchers set their sights on building general AI technologies that could impact hundreds of millions – or even billions – of people. But Dr. Danielle Bragg, a senior researcher at MSR’s New England lab, has a slightly smaller and more specific population in mind: the some seventy million people worldwide who use sign languages as their primary means of communication.


Today, Dr. Bragg gives us an insightful overview of the field and talks about the unique challenges and opportunities of building systems that expand access to information in line with the needs and desires of the deaf and signing community.


https://www.microsoft.com/research

MSR’s New York City lab is home to some of the best reinforcement learning research on the planet but if you ask any of the researchers, they’ll tell you they’re very interested in getting it out of the lab and into the real world. One of those researchers is Dr. Akshay Krishnamurthy and today, he explains how his work on feedback-driven data collection and provably efficient reinforcement learning algorithms is helping to move the RL needle in the real-world direction.


https://www.microsoft.com/research

Dr. Siddhartha Sen is a Principal Researcher in MSR’s New York City lab, and his research interests are, if not impossible, at least impossible sounding: optimal decision making, universal data structures, and verifiably safe AI.


Today, he tells us how he’s using reinforcement learning and HAIbrid algorithms to tap the best of both human and machine intelligence and develop AI that’s minimally disruptive, synergistic with human solutions, and safe.

This episode originally aired in August, 2018.


Kevin Scott has embraced many roles over the course of his illustrious career in technology: software developer, engineering executive, researcher, angel investor, philanthropist, and now, Chief Technology Officer of Microsoft. But perhaps no role suits him so well – or has so fundamentally shaped all the others – as his self-described role of “all-around geek.”


Today, in a wide-ranging interview, Kevin shares his insights on both the history and the future of computing, talks about how his impulse to celebrate the extraordinary people “behind the tech” led to an eponymous non-profit organization and a podcast, and… reveals the superpower he got when he was in grad school.


 

Dr. Devon Hjelm is a senior researcher at the Microsoft Research lab in Montreal, and today, he joins me to dive deep into his research on Deep InfoMax, a novel self-supervised learning approach to training AI models – and getting good representations – without human annotation. He also tells us how an interest in neural networks, first human and then machine, led to an inspiring career in deep learning research.


https://www.microsoft.com/research

This episode originally aired in June, 2019


You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.


On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.


https://www.microsoft.com/research


 

This episode originally aired in April, 2018


Emotions are fundamental to human interaction, but in a world where humans are increasingly interacting with AI systems, Dr. Mary Czerwinski, Principal Researcher and Research Manager of the Visualization and Interaction for Business and Entertainment group at Microsoft Research, believes emotions may be fundamental to our interactions with machines as well. And through her team’s work in affective computing, the quest to bring Artificial Emotional Intelligence – or AEI – to our computers may be closer than we think.


Today, Dr. Czerwinski tells us how a cognitive psychologist found her way into the research division of the world’s largest software company, suggests that rather than trying to be productive 24/7, we should aim for Emotional Homeostasis instead, and tells us how, if we do it right, our machines could become a sort of “emotional at-work DJ,” sensing and responding to our emotional states, and helping us to become happier and more productive at the same time.

This episode originally aired in April, 2019.


We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.


 


Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

This episode originally aired in December, 2017


On today’s episode, neuroscientist and virtual reality researcher, Dr. Mar Gonzalez Franco, talks about her work in VR, explains how avatars can help increase our empathy and reduce our biases via role play, and addresses the misconceptions that exist between the immersive experiences of virtual reality and psychedelic drugs.


Forty years ago, database research was an “exotic” field and, because of its business data processing reputation, was not considered intellectually interesting in academic circles. But that didn’t deter Dr. Philip Bernstein, now a Distinguished Scientist in MSR’s Data Management, Exploration and Mining group, and a pioneer in the field.


Today, Dr. Bernstein talks about his pioneering work in databases over the years and tells us all about Project Orleans, a distributed systems programming framework that makes life easier for programmers who aren’t distributed systems experts. He also talks about the future of database systems in a cloud scale world, and reveals where he finds his research sweet spot along the academic industrial spectrum.


https://www.microsoft.com/research

Brad Smith is the President of Microsoft and leads a team of more than 1400 employees in 56 countries. He plays a key role in spearheading the company’s work on critical issues involving the intersection of technology and society. In his spare time, he’s also an author!


We were fortunate to catch up with Brad who, late on a Friday afternoon, sat down with me in the booth to talk about his new book, Tools and Weapons: The Promise and the Peril of the Digital Age, and revealed the top ten tech policy issues he believes will shape our own century’s roaring 20s. He also gave us a peek inside the life of a person the New York Times has described a “de facto ambassador for the technology industry at large” – himself!


https://www.microsoft.com/research


 

Rangan Majumder is the Partner Group Program Manager of Microsoft’s Search and AI, and he has a simple goal: to make the world smarter and more productive. But nobody said simple was easy, so he and his team are working on better – and faster – ways to help you find the information you’re looking for, anywhere you’re looking for it.


Today, Rangan talks about how three big trends have changed the way Microsoft is building – and sharing – AI stacks across product groups. He also tells us about Project Turing, an internal deep learning moonshot that aims to harness the resources of the web and bring the power of deep learning to a search box near you.


https://www.microsoft.com/research


 

Dr. Behnaz Arzani is a senior researcher in the Mobility and Networking group at MSR, and she feels your pain. At least, that is, if you’re a network operator trying to troubleshoot an incident in a datacenter. Her research is all about getting networks to manage themselves, so your life is as pain-free as possible.


On today’s podcast, Dr. Arzani tells us why it’s so hard to identify and resolve networking problems and then explains how content-aware, or domain-customized, auto ML frameworks might help. She also tells us what she means when she says she wants to get humans out of the loop, and reveals how a competitive streak and a comment from her high school principal set her on the path to a career in high tech research.


https://www.microsoft.com/research


 

If you want an inside look at how a research idea goes from project to prototype to product, you should hang out with Gavin Jancke for a while. He’s the General Manager of Engineering for MSR Redmond where he created – and runs – the Central Engineering Group. Over the past two decades, he’s overseen more than seven hundred software and hardware engineering projects, from internal MSR innovations to Microsoft product group partnerships.


Today, Gavin takes us on a guided tour of the research engineering landscape and the engineering pipeline, recounting some of Central Engineering’s greatest hits. He also explains how the lab determines which projects get engineering resources, and reveals how one of his own projects ended up in the Museum of Modern Art.


https://www.microsoft.com/research


 

Over the past decade, the healthcare industry has undergone a series of technological changes in an effort to modernize it and bring it into the digital world, but the call for innovation persists. One person answering that call is Dr. Peter Lee, Corporate Vice President of Microsoft Healthcare, a new organization dedicated to accelerating healthcare innovation through AI and cloud computing.

Today, Dr. Lee talks about how MSR’s advances in healthcare technology are impacting the business of Microsoft Healthcare. He also explains how promising innovations like precision medicine, conversational chatbots and Azure’s API for data interoperability may make healthcare better and more efficient in the future.


https://www.microsoft.com/research

Dr. Debadeepta Dey is a Principal Researcher in the Adaptive Systems and Interaction group at MSR and he’s currently exploring several lines of research that may help bridge the gap between perception and planning for autonomous agents, teaching them make decisions under uncertainty and even to stop and ask for directions when they get lost!


On today’s podcast, Dr. Dey talks about how his latest work in meta-reasoning helps improve modular system pipelines and how imitation learning hits the ML sweet spot between supervised and reinforcement learning. He also explains how neural architecture search helps enlighten the “dark arts” of neural network training and reveals how boredom, an old robot and a several “book runs” between India and the US led to a rewarding career in research.


https://www.microsoft.com/research

Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research’s flagship lab in Redmond, it’s his job to inspire others to think big, too. But don’t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path.


On today’s podcast, Dr. Kossmann reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science… with marketing.


https://www.microsoft.com/research

In a world where productivity is paramount and only a handful of people have personal assistants, many of us are frustrated by the amount of time we spend in meetings, and worse, the amount time we spend planning, scheduling and rescheduling those meetings! Fortunately, Dr. Pamela Bhattacharya, a Principal Applied Scientist in Microsoft’s Outlook group, wants to turn your email into your own personal assistant. And a smart one at that!


Today, Dr. Bhattacharya tells us all about Scheduler, Microsoft’s virtual personal assistant, and how her team is using machine learning to put the “I” in intelligent PDAs. She also talks about how understanding different levels of automation can help us set the right expectations for our experience with AI, and explains how, in the workplace of the future, we might actually achieve more by doing less.


https://www.microsoft.com/research


 

There’s an old adage that says if you fail to plan, you plan to fail. But when it comes to AI, Dr. Saleema Amershi, a principal researcher in the Adaptive Systems and Interaction group at Microsoft Research, contends that if you plan to fail, you’re actually more likely to succeed! She’s an advocate of calling failure what it is, getting ahead of it in the AI development cycle and making end-users a part of the process.


Today, Dr. Amershi talks about life at the intersection of AI and HCI and does a little AI myth-busting. She also gives us an overview of what – and who – it takes to build responsible AI systems and reveals how a personal desire to make her own life easier may make your life easier too.


https://www.microsoft.com/research


 

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI.


Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way!


https://www.microsoft.com/research


 

Dr. Sriram Rajamani is a Distinguished Scientist and the Managing Director of the Microsoft Research lab in Bangalore. He’s dedicated his career to advancing globally applicable science in the testbed that is India. He is, by any measure, a world-class researcher and leader. He’s also, as you’ll find out shortly, a world-class storyteller!


Today, Dr. Rajamani talks about the unique challenges and opportunities of leading MSR’s research efforts in India and what it takes to build a robust research ecosystem in a country of huge disparities. He also dispels some preconceptions about poor and marginalized populations and explains why ‘frugal innovation’ may be one key to solving societal scale problems.


https://www.microsoft.com/research


 

This episode originally aired in May, 2019.


Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.


Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

This episode originally aired in May, 2019.


If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.


On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

This episode originally aired in May, 2019.Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.


Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

Dr. Sébastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.


Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.


https://www.microsoft.com/research

This episode first aired in November, 2018.


Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.


Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.


https://www.microsoft.com/research

With all the buzz surrounding AI, it can be tempting to envision it as a stand-alone entity that optimizes for accuracy and displaces human capabilities. But Dr. Besmira Nushi, a senior researcher in the Adaptive Systems and Interaction group at Microsoft Research, envisions AI as a cooperative entity that enhances human capabilities and optimizes for team performance.


On today’s podcast, Dr. Nushi talks about what it takes to develop collaborative AI systems and unpacks the unique challenges machine learning engineers face in their version of the software development cycle. She also reveals why understanding the “terrain of failure” can help researchers develop AI systems that perform as well in the real world as they do in the lab.


https://www.microsoft.com/research

Deep learning methodologies like supervised learning have been very successful in training machines to make predictions about the world. But because they’re so dependent upon large amounts of human-annotated data, they’ve been difficult to scale. Dr. Phil Bachman, a researcher at MSR Montreal, would like to change that, and he’s working to train machines to collect, sort and label their own data, so people don’t have to.


Today, Dr. Bachman gives us an overview of the machine learning landscape and tells us why it’s been so difficult to sort through noise and get to useful information. He also talks about his ongoing work on Deep InfoMax, a novel approach to self-supervised learning, and reveals what a conversation about ML classification problems has to do with Harrison Ford’s face.


https://www.microsoft.com/research


 

There’s a lot of excitement around self-driving cars, delivery drones, and other intelligent, autonomous systems, but before they can be deployed at scale, they need to be both reliable and safe. That’s why Gurdeep Pall, CVP of Business AI at Microsoft, and Dr. Ashish Kapoor, who leads research in Aerial Informatics and Robotics, are using a simulated environment called AirSim to reduce the time, cost and risk of the testing necessary to get autonomous agents ready for the open world.


Today, Gurdeep and Ashish discuss life at the intersection of machine learning, simulation and autonomous systems, and talk about the challenges we face as we transition from a world of automation to a world of autonomy. They also tell us about Game of Drones, an exciting new drone racing competition where the goal is to imbue flying robots with human-level perception and decision making skills… on the fly.


https://www.microsoft.com/research


 

Dr. Sumit Gulwani is a programmer’s programmer. Literally. A Partner Research Manager in the Program Synthesis, or PROSE, group at Microsoft Research, Dr. Gulwani is a leading researcher in program synthesis and the inventor of many intent-understanding, programming-by-example and programming-by-natural language technologies – aka, the automation of “what I meant to do and wanted to do, but my computer wouldn’t let me” tasks.


Today, Dr. Gulwani gives us an overview of the exciting “now” and promising future of program synthesis; reveals some fascinating new applications and technical advances; tells us the story behind the creation of Excel’s popular Flash Fill feature (and how a Flash Fill Fail elicited a viral tweet that paved the way for new domain investments); and shares a heartwarming story of how human empathy facilitated an “ah-ha math moment” in the life of a child, and what that might mean to computer scientists, educators and even tech companies in the future.


https://www.microsoft.com/research


 

Computer programming has often been perceived as the exclusive domain of computer scientists and software engineers. But that’s changing, thanks to the work of people like Dr. Thomas Ball, a Partner Researcher in the RiSE group at Microsoft Research, and Dr. Teddy Seyed, a post-doctoral researcher in the same group. Their goal is to make programming accessible to non-programmers in places like the classroom, the workshop… and even the runway!


On today’s podcast, Tom and Teddy talk about physical computing through platforms like MakeCode, a simplified programming environment that makes it easier for young people – and other computer science neophytes – to start coding with programmable microcontrollers. They also tell us all about Project Brookdale, where they did a collaborative fashion show that gave emerging designers the tools to embed technology in their garments and produce wearables you’d actually want to be seen in!


https://www.microsoft.com/research


 

Remember when a hard drive that could hold a terabyte of data was a big deal? Well, we’re now in an era where peta-, exa- and even zetta-bytes are the bytes of the day, and it turns out it’s hard to fit that many zeroes on a hard drive. That’s where Dr. Ant Rowstron, Deputy Lab Director of Microsoft Research Cambridge, and Mark Russinovich, Chief Technical Officer of Azure, come in. Their respective teams are working on paradigm-breaking solutions to give us phenomenal storage power in an itty-bitty living space.


Today, Ant and Mark discuss their roles in the development of new optical technologies, like Project Silica, for cloud-scale storage demands, and talk about the Optics for the Cloud Research Alliance, an exciting new collaboration between academic researchers and MSR. They also explain how just the right mix of innovation and engineering can make the cloud more powerful and less expensive to use and, at the same time, deliver “forever” storage that’s both dishwasher and microwave safe!


https://www.microsoft.com/research

Jenny Sabin is an architectural designer, a professor, a studio principal and MSR’s current Artist in Residence. Asta Roseway is a principal research designer, a “fusionist” and the co-founder of the Artist in Residence program at Microsoft Research. The two, along with a stellar multi-disciplinary team, recently completed the installation of Ada, the first interactive architectural pavilion powered by AI, in the heart of the Microsoft Research building in Redmond.


On today’s podcast, Jenny and Asta talk about life at the intersection of art and science; tell us why the Artist in Residence program pushes the boundaries of technology in unexpected ways; and reveal their vision of the future of bio-inspired, human-centered, AI-infused architecture.


https://www.microsoft.com/research

Machine learning is a powerful tool that enables conversational agents to provide general question-answer services. But in domains with more specific taxonomies – or simply for requests that are longer and more complicated than “Play Baby Shark” – custom conversational AI has long been the province of large enterprises with big budgets. But not for long, thanks to the work of Dr. Riham Mansour, a Principal Software Engineering Manager for Microsoft’s Language Understanding Service, or LUIS. She and her colleagues are using the emerging science of machine teaching to help domain experts build bespoke AI models with little data and no machine learning expertise.


On today’s podcast, Dr. Mansour gives us a brief history of conversational machines at Microsoft; tells us all about LUIS, one of the first Microsoft products to deploy machine teaching concepts in real world verticals; and explains how an unlikely combination of engineering skills, science skills, entrepreneurial skills – and not taking no for an answer – helped make automated customer engagement and business functions more powerful, more accessible and more intelligent!


https://www.microsoft.com/research

Dr. Craig Costello is in the business of safeguarding your secrets. And he uses math to do it. A researcher in the Security and Cryptography group at Microsoft Research, Dr. Costello is among a formidable group of code makers (aka cryptographers) who make it their life’s work to protect the internet against adversarial code breakers (aka cryptanalysts), both those that exist today in our classical computing world, and those that will exist in a quantum computing future.


On today’s podcast, Dr. Costello gives us a battlefield update in the ongoing crypto wars; talks about different approaches to post quantum cryptography and explains why he believes isogeny-based primitives are among the most promising; and reassures us that, as long as the battle goes on, cryptographers will continue to work very hard on the very hard math they hope will protect us from hackers and attackers, even in the age of quantum computers. https://www.microsoft.com/research

Using technology to help us improve our health is nothing new: a quick web search returns hundreds of apps and devices claiming to help us get fit, quit smoking, master anxiety or just “find our center.” What is new is a serious cohort of researchers exploring how artificial emotional intelligence, or AEI, could help us understand ourselves better and, when used in concert with human caregivers, enhance our well-being. One of those researchers is Jina Suh, a former Xbox developer who got hooked on research and is now an RSDE in the Human Understanding and Empathy group at MSR, as well as a PhD student in computer science at the University of Washington.


On today’s podcast, Jina shares her passion for creating technologies that promote emotional resilience and mental health; gives us an inside look at an innovative research collaboration that aims to improve collaborative care for cancer patients with depression; and tells us an emotional story of how, on the brink of quitting her job, she found inspiration to get back in the game and begin a new career in research for human well-being. https://www.microsoft.com/research

If someone asked you what snow leopards and Vincent Van Gogh have in common, you might think it was the beginning of a joke. It’s not, but if it were, Mark Hamilton, a software engineer in Microsoft’s Cognitive Services group, budding PhD student and frequent Microsoft Research collaborator, would tell you the punchline is machine learning. More specifically, Microsoft Machine Learning for Apache Spark (MMLSpark for short), a powerful yet elastic open source machine learning library that’s finding its way beyond business and into “AI for Good” applications such as the environment and the arts.


Today, Mark talks about his love of mathematics and his desire to solve big, crazy, core knowledge sized problems; tells us all about MMLSpark and how it’s being used by organizations like the Snow Leopard Trust and the Metropolitan Museum of Art; and reveals how the persuasive advice of a really smart big sister helped launch an exciting career in AI research and development.


https://www.microsoft.com/research


 

Dr. Eyal Ofek is a senior researcher at Microsoft Research and his work deals mainly with, well, reality. Augmented and virtual reality, to be precise. A serial entrepreneur before he came to MSR, Dr. Ofek knows a lot about the “long nose of innovation” and what it takes to bring a revolutionary new technology to a world that’s ready for it.


On today’s podcast, Dr. Ofek talks about the unique challenges and opportunities of augmented and virtual reality from both a technical and social perspective; tells us why he believes AR and VR have the potential to be truly revolutionary, particularly for people with disabilities; explains why, while we’re doing pretty well in the virtual worlds of sight and sound, our sense of virtual touch remains a bit more elusive; and reveals how, if he and his colleagues are wildly successful, it won’t be that long before we’re living in a whole new world of extension, expansion, enhancement and equality.https://www.microsoft.com/research

Dr. Susan Dumais knows you have things to do, and if you need help finding stuff to get them done (and you probably do) then her long and illustrious career in search technologies has been worth it. Situated firmly in Louis Pasteur’s quadrant of the research grid (the square where you answer “yes” to both the quest for fundamental understanding and use-based applications) the Microsoft Technical Fellow, and Deputy Lab Director of MSR AI, has made finding information the focus of her career, and has probably made your life a little more productive in the process.


Today, Dr. Dumais tells us how the landscape of information retrieval has evolved over the past twenty years; reminds us that queries don’t fall from the sky but are grounded in the context of real people, real events and real time; talks about her current interest in non-web-based search (or how I can easily put my hands on my own digital belongings) and reveals what apples and Michael Jordan have in common with search research.https://www.microsoft.com/research

In 2018, Microsoft launched the Microsoft AI Residency Program, a year-long, expanded research experience designed to give recent graduates in a variety of fields the opportunity to work alongside prominent researchers at MSR on cutting edge AI technologies to solve real-world problems. Dr. Brian Broll was one of them. A newly minted PhD in Computer Science from Vanderbilt University, Dr. Broll was among the inaugural cohort of AI residents who spent a year working on machine learning in game environments and is on the pod to talk about it!


Today, Dr. Broll gives us an overview of the work he did and the experience he had as a Microsoft AI Resident, talks about his passion for making complex concepts easier and more accessible to novices and young learners, and tells us how growing up on a dairy farm in rural Minnesota helped prepare him for a life in computer science solving some of the toughest problems in AI.


 


https://www.microsoft.com/research

Dr. Ed Cutrell is a Principal Researcher in the Ability group at Microsoft Research and he’s convinced that great technology should be available to everyone. Working in the fields of Accessibility and Information and Communication Technologies for Development (aka ICT4D), his research has explored computing solutions for people across the resource and ability spectrum, both here and around the world.


Today, Dr. Cutrell gives us an overview of his work in the disability and inclusive design space, explains the vital importance of interdisciplinarity – a fancy way of saying many ways of thinking and many ways of knowing – and tells us how a dumb phone beat a smart tablet in rural India… and what that meant to researchers.


https://www.microsoft.com/research


 

As computing moves to the cloud, there is an increasing need for privacy in AI. In an ideal world, users would have the ability to compute on encrypted data without sacrificing performance. Enter Dr. Olli Saarikivi, a post-doctoral researcher in the RiSE group at MSR. He, along with a stellar group of cross-disciplinary colleagues, are bridging the gap with CHET, a compiler and runtime for homomorphic evaluation of tensor programs, that keeps data private while making the complexities of homomorphic encryption schemes opaque to users.


On today’s podcast, Dr. Saarikivi tells us all about CHET, gives us an overview of some of his other projects, including Parasail, a novel approach to parallelizing seemingly sequential applications, and tells us how a series of unconventional educational experiences shaped his view of himself, and his career as a researcher. https://www.microsoft.com/research

The ability to read and understand unstructured text, and then answer questions about it, is a common skill among literate humans. But for machines? Not so much. At least not yet! And not if Dr. T.J. Hazen, Senior Principal Research Manager in the Engineering and Applied Research group at MSR Montreal, has a say. He’s spent much of his career working on machine speech and language understanding, and particularly, of late, machine reading comprehension, or MRC.


On today’s podcast, Dr. Hazen talks about why reading comprehension is so hard for machines, gives us an inside look at the technical approaches applied researchers and their engineering colleagues are using to tackle the problem, and shares the story of how an a-ha moment with a Rubik’s Cube inspired a career in computer science and a quest to teach computers to answer complex, text-based questions in the real world.


https://microsoft.com/research

In an era of unprecedented advances in AI and machine learning, current gen systems and networks are being challenged by an unprecedented level of complexity and cost. Fortunately, Dr. Ganesh Ananthanarayanan, a researcher in the Mobility and Networking group at MSR, is up for a challenge. And, it seems, the more computationally intractable the better! A prolific researcher who’s interested in all aspects of systems and networking, he’s on a particular quest to extract value from live video feeds and develop “killer apps” that will have a practical impact on the world.


Today, Dr. Ananthanarayanan tells us all about Video Analytics for Vision Zero (an award-winning “killer app” that aims to reduce traffic-related fatalities to zero), gives us a wide-angle view of his work in geo-distributed data analytics and client-cloud networking, and explains how the duration and difficulty of a Test Cricket match provides an invaluable lesson for success in life and research.


https://www.microsoft.com/research

Dr. Nathalie Riche envisions a future in which all of our data will be accessible, meaningful, compelling and artistic. And as a researcher in human computer interaction and information visualization at Microsoft Research, she’s working on technical tools that will help us wrangle our data, extract knowledge from it, and communicate with it in a memorable, persuasive and aesthetically pleasing way. In other words, she wants our data to be both smart… and beautiful!


Today, Dr. Riche shares her passion for the art of data driven storytelling, reveals the two superpowers of data visualization, gives us an inside look at some innovative projects designed to help us th(ink) with digital ink, and tells the story of how a young woman with an artist’s heart headed into computer science, took a detour to the beach, paid for it with research and ended up with a rewarding career that brings both art and computing together.


https://www.microsoft.com/research


 

This episode first aired in January, 2018. When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.


https://www.microsoft.com/research

This episode first aired in March, 2018. There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it.Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.


https://www.microsoft.com/research

Dr. Johannes Gehrke is a Microsoft Technical Fellow and head of Architecture and Machine Learning for the Intelligent Communications and Conversations Cloud in Microsoft’s Experiences and Devices division. But lest you think his lofty position makes him in any way superior to you, let me tell you, he knows who works for whom, and he’ll be the first to tell you that you are his boss!


On today’s podcast, Dr. Gehrke frames the new, cloud-powered work world as a fast paced, widely-distributed workplace that demands real-time decision-making and collaboration – and explains how products like Microsoft Teams are meeting those demands – and tells us, both directly and indirectly, about the future of work, which for Microsoft, involves a pivot from an app-centric approach to a people-centric approach where, by using an AI-infused productivity suite coupled with the power of the cloud, we can essentially “hire Microsoft” to help us get our work done.

This episode first aired in November, 2017 - Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counterintuitive.Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of 4 young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks – could help us be more productive, and experience a better quality of life at the same time.https://microsoft.com/research

This episode first aired in January, 2018. As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”


https://www.microsoft.com/research

If you’re like me, you’re no longer amazed by how all your technologies can work for you. Rather, you’ve begun to take for granted that they simply should work for you. Instantly. All together. All the time. The fact that you’re not amazed is a testimony to the work that people like Dr. Lidong Zhou, Assistant Managing Director of Microsoft Research Asia, do every day. He oversees some of the cutting-edge systems and networking research that goes on behind the scenes to make sure you’re not amazed when your technologies work together seamlessly but rather, can continue to take it for granted that they will!


Today, Dr. Zhou talks about systems and networking research in an era of unprecedented systems complexity and what happens when old assumptions don’t apply to new systems, explains how projects like CloudBrain are taking aim at real-time troubleshooting to address cloud-scale, network-related problems like “gray failure,” and tells us why he believes now is the most exciting time to be a systems and networking researcher.

Dr. Chris Bishop is a Microsoft Technical Fellow and director of MSR Cambridge, where he oversees an impressive portfolio of research including machine learning, AI, healthcare and gaming. Phil Spencer is the Executive Vice President of Gaming at Microsoft where he oversees everything from the design of the next Xbox console to the creation and release of blockbuster properties like Halo, Gears of War and Forza Motorsport. These two powerhouse executives are pushing the boundaries of creativity, technical innovation and fun across the spectrum of gaming genres and devices for nearly 2 billion gamers around the world.


On today’s podcast, Chris and Phil discuss their respective roles in Microsoft’s gaming ecosystem, revealing a sort of “enrichment pipeline” that flows all the way from researcher to developer to gamer. They also give us an inside look at the close collaboration between the world-class research organization of MSR and the world-class gaming franchise of Xbox, highlighting Microsoft’s unique ability to deliver the tools, talent and resources that fuel innovation and help shape the future of gaming.http://www.microsoft.com/research

You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.


On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.

If you’ve recently found it more difficult to focus your attention for a lengthy stretch of time in order to get a complex task done… or worse, found it difficult even to find a lengthy stretch of time in which to try, you’re not alone. And actually, you’re in luck. Dr. Shamsi Iqbal, a senior researcher in the Information and Data Sciences group at Microsoft Research, wants to help you manage your attention better and be more productive at the same time. And she’s using technology to do it!


On today’s podcast, Dr. Iqbal tells us about her work in the field of micro-productivity, a line of research that takes aim at the short spurts of time she calls micro-moments that we otherwise might have considered too short to get anything useful done. She also explains why distraction can be good for us and gives us some advice on how to make the most of our cognitive resources, whether by setting aside time to tackle big tasks in the traditional way or by breaking them down into micro-tasks… and “outsourcing” them to ourselves!

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.


Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.


On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

When was the last time you had a meaningful conversation with your computer… and felt like it truly understood you? Well, if Dr. Xuedong Huang, a Microsoft Technical Fellow and head of Microsoft’s Speech and Language group, is successful, you will. And if his track record holds true, it’ll be sooner than you think!


On today’s podcast, Dr. Huang talks about his role as Microsoft’s Chief Speech Scientist, gives us some inside details on the latest milestones in speech and language technology, and explains how mastering speech recognition, translation and conversation will move machines further along the path from “perceptive AI” to “cognitive AI” and that much closer to truly human intelligence.

Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.


Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

If you want to know what’s going on in the world of human computer interaction research, or what’s new at the CHI Conference on Human Factors in Computing Systems, you should hang out with Dr. Ken Hinckley, a principal researcher and research manager in the EPIC group at Microsoft Research, and Dr. Merrie Ringel Morris, a principal researcher and research manager in the Ability group. Both are prolific HCI researchers who are seeking, from different angles, to augment the capability of technologies and improve the experiences people have with them.


On today’s podcast, we get to hang out with both Dr. Hinckley and Dr. Morris as they talk about life at the intersection of hardware, software and human potential, discuss how computers can enhance human lives, especially in some of the most marginalized populations, and share their unique approaches to designing and building technologies that really work for people and for society.

In the world of relational databases, structured query language, or SQL, has long been King of the Queries, primarily because of its ubiquity and unparalleled performance. But many users prefer a mix of imperative programming, along with declarative SQL, because its user-defined functions (or UDFs) allow for good software engineering practices like modularity, readability and re-usability. Sadly, these benefits have traditionally come with a huge performance penalty, rendering them impractical in most situations. That bothered Dr. Karthik Ramachandra, a Senior Applied Scientist at Microsoft Research India, so he’s spent a great deal of his career working on improving an imperative complement to SQL in database systems.


Today, Dr. Ramachandra gives us an overview of the historic trade-offs between declarative and imperative programming paradigms, tells us some fantastic stories, including The Tale of Two Engineers and The UDF Story, Parts 1 and 2, and introduces us to Froid – that’s F-R-O-I-D, not the Austrian psychoanalyst – which is an extensible, language-agnostic framework for optimizing imperative functions in databases, offering the benefits of UDFs without sacrificing performance.

We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.


Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

 


Dr. Marc Pollefeys is a Professor of Computer Science at ETH Zurich, a Partner Director of Science for Microsoft, and the Director of a new Microsoft Mixed Reality and AI lab in Switzerland. He’s a leader in the field of computer vision research, but it’s hard to pin down whether his work is really about the future of computer vision, or about a vision of future computers. Arguably, it’s both!


On today’s podcast, Dr. Pollefeys brings us up to speed on the latest in computer vision research, including his innovative work with Azure Spatial Anchors, tells us how devices like Kinect and HoloLens may have cut their teeth in gaming, but turned out to be game changers for both research and industrial applications, and explains how, while it’s still early days now, in the future, you’re much more likely to put your computer on your head than on your desk or your lap.

Ann Paradiso is an interaction designer and the Principal User Experience Designer for the NExT Enable group at Microsoft Research. She’s also the epitome of a phrase she often uses to describe other people: a force of nature. Together with a diverse array of team members and collaborators, many of whom have ALS or other conditions that affect mobility and speech, Ann works on new interaction paradigms for assistive technologies hoping to make a more bespoke approach to technology solutions accessible, at scale, to the people who need it most.


On today’s podcast, Ann tells us all about life in the extreme constraint design lane, explains what a PALS is, and tells us some incredibly entertaining stories about how the eye tracking technology behind the Eye Controlled Wheelchair and the Hands-Free Music Project has made its way from Microsoft’s campus to some surprising events around the country, including South by Southwest and Mardi Gras.

This episode first aired in September, 2018:


You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, Massachusetts, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.


On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning – now a feature of Azure Machine Learning – that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

If you’ve ever played video games, you know that for the most part, they look a lot better than they sound. That’s largely due to the fact that audible sound waves are much longer – and a lot more crafty – than visual light waves, and therefore, much more difficult to replicate in simulated environments. But Dr. Nikunj Raghuvanshi, a Senior Researcher in the Interactive Media Group at Microsoft Research, is working to change that by bringing the quality of game audio up to speed with the quality of game video. He wants you to hear how sound really travels – in rooms, around corners, behind walls, out doors – and he’s using computational physics to do it.


Today, Dr. Raghuvanshi talks about the unique challenges of simulating realistic sound on a budget (both money and CPU), explains how classic ideas in concert hall acoustics need a fresh take for complex games like Gears of War, reveals the computational secret sauce you need to deliver the right sound at the right time, and tells us about Project Triton, an acoustic system that models how real sound waves behave in 3-D game environments to makes us believe with our ears as well as our eyes.

When we think of information processing systems, we often think of computers, but we ourselves are made up of information processing systems – trillions of them – also known as the cells in our bodies. While these cells are robust, they’re also extraordinarily complex and not altogether predictable. Wouldn’t it be great, asks Dr. Andrew Phillips, head of the Biological Computation Group at Microsoft Research in Cambridge, if we could figure out exactly how these building blocks of life work and harness their power with the rigor and predictability of computer science? To answer that, he’s spent a good portion of his career working to develop a system of intelligence that can, literally, program biology.


Today, Dr. Phillips talks about the challenges and rewards inherent in reverse engineering biological systems to see how they perform information processing. He also explains what we can learn from stressed out bacteria, and tells us about Station B, a new end-to-end platform his team is working on that aims to reduce the trial and error nature of lab experiments and help scientists turn biological cells into super-factories that could solve some of the most challenging problems in medicine, agriculture, the environment and more.

This episode first aired in August of 2018.


You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.


 

If you’ve ever wondered why, in the age of the internet, we still don’t hold our elections online, you need to spend more time with Dr. Josh Benaloh, Senior Cryptographer at Microsoft Research in Redmond. Josh knows a lot about elections, and even more about homomorphic encryption, the mathematical foundation behind the end-to-end verifiable election systems that can dramatically improve election integrity today and perhaps move us toward wide-scale online voting in the future.


Today, Dr. Benaloh gives us a brief but fascinating history of elections, explains how the trade-offs among privacy, security and verifiability make the relatively easy math of elections such a hard problem for the internet, and tells the story of how the University of Michigan fight song forced the cancellation of an internet voting pilot.

Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you’d talk to another person. That’s the easy part. The hard part is getting your machine to understand and talk back to you like it’s that other person.


Today, Dr. El Asri talks about the particular challenges she and other scientists face in building sophisticated dialogue systems that lay the foundation for talking machines. She also explains how reinforcement learning, in the form of a text game generator called TextWorld, is helping us get there, and relates a fascinating story from more than fifty years ago that reveals some of the safeguards necessary to ensure that when we design machines specifically to pass the Turing test, we design them in an ethical and responsible way.

If every question in life could be answered by choosing from just a few options, machine learning would be pretty simple, and life for machine learning researchers would be pretty sweet. Unfortunately, in both life and machine learning, things are a bit more complicated. That’s why Dr. Manik Varma, Principal Researcher at MSR India, is developing extreme classification systems to answer multiple-choice questions that have millions of possible options and help people find what they are looking for online more quickly, more accurately and less expensively.


On today’s podcast, Dr. Varma tells us all about extreme classification (including where in the world you might actually run into 10 or 100 million options), reveals how his Parabel and Slice algorithms are making high quality recommendations in milliseconds, and proves, with both his life and his work, that being blind need not be a barrier to extreme accomplishment.

Haiyan Zhang is a designer, technologist and maker of things (really cool technical things) who currently holds the unusual title of Innovation Director at the Microsoft Research lab in Cambridge, England. There, she applies her unusual skillset to a wide range of unusual solutions to real-life problems, many of which draw on novel applications of gaming technology in serious areas like healthcare.


On today’s podcast, Haiyan talks about her unique “brain hack” approach to the human-centered design process, and discusses a wide range of projects, from the connected play experience of Zanzibar, to Fizzyo, which turns laborious breathing exercises for children with cystic fibrosis into a video game, to Project Emma, an application of haptic vibration technology that, somewhat curiously, offsets the effects of tremors caused by Parkinson’s disease.

From his deep technical roots as a principal researcher and founder of the Communications, Collaboration and Signal Processing group at MSR, through his tenure as Managing Director of the lab in Redmond, to his current role as Distinguished Engineer, Chief Scientist for Microsoft Research and manager of the MSR NExT Enable group, Dr. Rico Malvar has seen – and pretty well done – it all.


Today, Dr. Malvar recalls his early years at a fledgling Microsoft Research, talks about the exciting work he oversees now, explains why designing with the user is as important as designing for the user, and tells us how a challenge from an ex-football player with ALS led to a prize winning hackathon project and produced the core technology that allows you to type on a keyboard without your hands and drive a wheelchair with your eyes.

You never know how an incident in your own life might inspire a breakthrough in science, but Dr. Cecily Morrison, a researcher in the Human Computer Interaction group at Microsoft Research Cambridge, can attest to how even unexpected events can cause us to see things through a different – more inclusive – lens and, ultimately, give rise to innovations in research that impact everyone.


On today’s podcast, Dr. Morrison gives us an overview of what she calls the “pillars” of inclusive design, shares how her research is positively impacting people with health issues and disabilities, and tells us how having a child born with blindness put her in touch with a community of people she would otherwise never have met, and on the path to developing Project Torino, an inclusive physical programming language for children with visual impairments.

The entertainment industry has long offered us a vision of the perfect personal assistant: one that not only meets our stated needs but anticipates needs we didn’t even know we had. But these uber-assistants, from the preternaturally prescient Radar O’Reilly in the TV show M.A.S.H. to Tony Stark’s digital know-and-do-it-all Jarvis in Iron Man, have always lived in the realm of fiction or science fiction. That could all change, if Dr. Paul Bennett, Principal Researcher and Research Manager of the Information and Data Sciences group at Microsoft Research, has anything to say about it. He and his team are working to make machines “calendar and email aware,” moving intelligent assistance into the realm of science and onto your workstation.


Today, Dr. Bennett brings us up to speed on the science of contextually intelligent assistants, explains how what we think our machines can do actually shapes what we expect them to do, and shares how current research in machine learning and data science is helping machines reason on our behalf in the quest to help us find the right information effortlessly.

When people first started making software, computers were relatively rare and there was no internet, so programming languages were designed to get the job done quickly and run efficiently, with little thought for security. But software is everywhere now, from our desktops to our cars, from the cloud to the internet of things. That’s why Dr. Jonathan Protzenko, a researcher in the RiSE – or Research in Software Engineering – group at Microsoft Research, is working on designing better software tools in order to make our growing software ecosystem safer and more secure.


Today, Dr. Protzenko talks about what’s wrong with software (and why it’s vitally important to get it right), explains why there are so many programming languages (and tells us about a few he’s been working on), and finally, acts as our digital Sherpa for Project Everest, an assault on software integrity and confidentiality that aims to build and deploy a verified HTTPS stack.

The episode first aired in May, 2018.In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

This episode first aired in January, 2018.When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.


Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.

This episode first aired in March, 2018.Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.

Amos Miller is a product strategist on the Microsoft Research NeXT Enable team, and he’s played a pivotal role in bringing some of MSR’s most innovative research to users with disabilities. He also happens to be blind, so he can appreciate, perhaps in ways others can’t, the value of the technologies he works on, like Soundscape, an app which enhances mobility independence through audio and sound.


On today’s podcast, Amos Miller answers burning questions like how do you make a microwave accessible, what’s the cocktail party effect, and how do you hear a landmark? He also talks about how researchers are exploring the untapped potential of 3D audio in virtual and augmented reality applications, and explains how, in the end, his work is not so much about making technology more accessible, but using technology to make life more accessible.

Dr. Sebastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.


Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.

Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.


Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.

This episode first aired in March (2018)One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions.


Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.


 

After decades of research in processing audio signals, we’ve reached the point of so-called performance saturation. But recent advances in machine learning and signal processing algorithms have paved the way for a revolution in speech recognition technology and audio signal processing. Dr. Ivan Tashev, a Partner Software Architect in the Audio and Acoustics Group at Microsoft Research, is no small part of the revolution, having both published papers and shipped products at the forefront of the science of sound.


On today’s podcast, Dr. Tashev gives us an overview of the quest for better sound processing and speech enhancement, tells us about the latest innovations in 3D audio, and explains why the research behind audio processing technology is, thanks to variations in human perception, equal parts science, art and craft.

In 1998, Microsoft Research opened a small lab in Beijing to expand its research efforts and draw on the immense high-tech talent pool in China. No one expected that only twenty years later, MSR Asia would become the dynamic organization it is today, with innovative research contributing to nearly every part of Microsoft’s business. Dr. Hsiao-Wuen Hon has watched it grow from the beginning and this year, celebrates the lab’s 20th anniversary as Managing Director, Corporate Vice President and Chairman of Microsoft’s Asia-Pacific R&D Group.


On today’s podcast, Dr. Hon gives us a brief history of MSR Asia, from its humble beginnings to its significant role in the AI boom today, talks about MSR Asia’s unique talent pipeline, shares his vision for the complementary roles of machine intelligence and human wisdom, and explains why, he believes, the more progress we make in AI, the better we understand ourselves.

As traditional semiconductor technologies for computer storage scale down, everyone is looking for alternative solutions to the growing gap between the amount of data we’re capable of producing and the amount of data we’re capable of storing. While some have focused on hardware accelerators for machine learning, and others are investigating new memory technologies, Dr. Karin Strauss, a Senior Researcher at Microsoft Research in Redmond, has been exploring the role of biotechnology in IT via an end-to-end system that stores digital data in DNA.


On today’s podcast, Dr. Strauss talks about life at the intersection of computer science and biology which, for many, is more like the intersection of science fiction and science, and explains how the unique properties of DNA could eventually enable us to store really big data in really small places for a really long time.

 


The ancient Chinese philosopher Confucius famously exhorted his pupils to study the past if they would divine the future. In 2018, we get the same advice from a decidedly more modern, but equally philosophical Bill Buxton, Principal Researcher in the HCI group at Microsoft Research. In addition to his pioneering work in computer science and design, Bill Buxton has spent the past several decades amassing a collection of more than a thousand artifacts that chronicle the history of human computer interaction for the very purpose of informing the future of human computer interaction.


Today, in a wide-ranging interview, Bill Buxton explains why Marcel Proust and TS Eliot can be instructive for computer scientists, why the long nose of innovation is essential to success in technology design, why problem-setting is more important than problem-solving, and why we must remember, as we design our technologies, that every technological decision we make is an ethical decision as well.

2018 marks the 10th anniversary of Microsoft Research New England in Cambridge, Massachusetts, so it’s the perfect time to talk with someone who was there from the lab’s beginning: Technical Fellow, Managing Director and Co-founder, Dr. Jennifer Chayes. But not only does Dr. Chayes run the New England lab of MSR, she also directs two other highly renowned, interdisciplinary research labs in New York City and Montreal, Quebec. Add to that a full slate of personal research projects and service on numerous boards, committees and foundations, and you’ve got one of the busiest and most influential women in high tech.


On today’s podcast, Dr. Chayes shares her passion for the value of undirected inquiry, talks about her unlikely journey from rebel to researcher, and explains how she believes her research philosophy – more botanist than boss – prepares the fertile ground necessary for important, innovative and impactful research.

Asta Roseway has a formal title. It’s Principal Research Designer in the HCI group at Microsoft Research. But she’s also been described as a conductor, an alchemist, a millennial in a Gen-Xer’s body and, in her own words, a fusionist. What’s a fusionist, you might ask? Well, you’re about to find out.


On today’s podcast, Asta gives an inside look at one of the most unconventional labs at Microsoft Research. Located at the intersection of science, technology and art, it’s a lab that insists that technology, like art, should push boundaries, tell stories and feed our souls. Get ready for the unexpected because when Asta asks “what if?” you’re likely to find yourself immersed in a world of responsive clothing, smart tattoos, talking plants and even environmentally sensitive… makeup!

You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, MA, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.


On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning - now a feature of Azure Machine Learning - that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

At the heart of any vibrant research community, you’ll find a diverse range of scientists. You’re also likely to find a robust internship program, like the one at Microsoft Research. This summer, MSR welcomed another stellar group of interns who had the opportunity to learn, collaborate, and network with colleagues and mentors who will impact their lives for years to come.


On today’s podcast, you’ll hear the stories of three of these interns, each of whom came to Microsoft Research from a different field, with a different story and a different perspective, but all of whom share MSR’s passion for finding innovative solutions to the world’s toughest challenges.

Dr. Nancy Baym is a communication scholar, a Principal Researcher in MSR’s Cambridge, Massachusetts, lab, and something of a cyberculture maven. She’s spent nearly three decades studying how people use communication technologies in their everyday relationships and written several books on the subject. The big take away? Communication technologies may have changed drastically over the years, but human communication itself? Not so much.


Today, Dr. Baym shares her insights on a host of topics ranging from the arduous maintenance requirements of social media, to the dialectic tension between connection and privacy, to the funhouse mirror nature of emerging technologies. She also talks about her new book, Playing to the Crowd: Musicians, Audiences and the Intimate Work of Connection, which explores how the internet transformed – for better and worse – the relationship between artists and their fans.

Datacenters have a hard time keeping their cool. Literally. And with more and more datacenters coming online all over the world, calls for innovative solutions to “cool the cloud” are getting loud. So, Ben Cutler and the Special Projects team at Microsoft Research decided to try to beat the heat by using one of the best natural venues for cooling off on the planet: the ocean. That led to Project Natick, Microsoft’s prototype plan to deploy a new class of eco-friendly datacenters, under water, at scale, anywhere in the world, from decision to power-on, in 90 days. Because, presumably for Special Projects, go big or go home.


In today’s podcast we find out a bit about what else the Special Projects team is up to, and then we hear all about Project Natick and how Ben and his team conceived of, and delivered on, a novel idea to deal with the increasing challenges of keeping datacenters cool, safe, green, and, now, dry as well!

The wildly popular video game, Minecraft, might appear to be an unlikely candidate for machine learning research, but to Dr. Katja Hofmann, the research lead of Project Malmo in the Machine Intelligence and Perception Group at Microsoft Research in Cambridge, England, it’s the perfect environment for teaching AI agents, via reinforcement learning, to act intelligently – and cooperatively – in the open world.


Today, Dr. Hofmann talks about her vision of a future where machines learn to collaborate with people and empower them to help solve complex, real-world problems. She also shares the story of how her early years in East Germany, behind the Iron Curtain, shaped her both personally and professionally, and ultimately facilitated a creative, exploratory mindset about computing that informs her work to this day.

You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.


Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.

If your idea of a great job includes pursuing untethered research, shepherding brilliant researchers and helping shape the long-term strategy of one of the largest tech companies in the world… oh, and also publishing prolifically, authoring patents, winning awards and speaking around the world… you are in good company. That’s what Dr. Victor Bahl, Distinguished Scientist and Director of Mobility and Networking at Microsoft Research, does for a living. And he loves it!


Today, in our first live podcast, recorded at MSR’s 2018 Faculty Summit, Dr. Bahl shares some fascinating stories from his long and illustrious career, gives us an inside look at what’s new in networking, and, explains why, in an industry where it pays to be the smartest person in the room, it’s important to be a world-class listener.

Kevin Scott has embraced many roles over the course of his illustrious career in technology: software developer, engineering executive, researcher, angel investor, philanthropist, and now, Chief Technology Officer of Microsoft. But perhaps no role suits him so well – or has so fundamentally shaped all the others – as his self-described role of “all-around geek.”


Today, in a wide-ranging interview, Kevin shares his insights on both the history and the future of computing, talks about how his impulse to celebrate the extraordinary people “behind the tech” led to an eponymous non-profit organization and a podcast, and… reveals the superpower he got when he was in grad school.

Dr. Lenin Ravindranath Sivalingam is a researcher by trade, but by nature, he’s an entrepreneur, and a hacker with a heart of gold. It’s this combination of skill and passion that informs his work at Microsoft Research, driving him to discover and build tools that will make life both easier for developers and better for end-users.


Today, Dr. Ravindranath Sivalingam tells us why he is so passionate about what he does, explains how internships can literally change your life, and shares the story of how a hackathon idea turned into a prize-winning project… and then became the backbone of a powerhouse tool for gamers and their fans.


To learn more about Dr. Ravindranath Sivalingam, and how Microsoft researchers are working to make life more easier and more robust for everyone, visit Microsoft.com/research

First aired on January 17, 2018. If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC – group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality.Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.

First aired on December 4th, 2017. When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Dr. Horvitz talks about the goal of artificial intelligence, his vision for our collaborative future with machines, what we can learn from the Wright brothers, and how a short stint of “six months, maximum” became an illustrious and, in his words, joyful, 25-year career at Microsoft Research.

This episode first aired in January (2018).In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is… a programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

This episode first aired in April (2018). When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming.Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your wi-fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

Developing complex artificial intelligence systems in a lab is a challenging task, but what happens when they go into production and interact with real humans? That’s what researchers like Dr. Fernando Diaz, a Principal Research Manager at Microsoft Research Montreal, want to know. He and his colleagues are trying to understand – and address – the social implications of these systems as they enter the open world.


Today, Dr. Diaz shares his insights on the kinds of questions we need to be asking about artificial intelligence and its impact on society. He also talks about how algorithms can affect your taste in music, and why now, more than ever, computer science education needs to teach ethics along with algorithms.

This episode first aired in November (2017). Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.

In technical terms, computer vision researchers “build algorithms and systems to automatically analyze imagery and extract knowledge from the visual world.” In layman’s terms, they build machines that can see. And that’s exactly what Principal Researcher and Research Manager, Dr. Gang Hua, and Computer Vision Technology team, are doing. Because being able to see is really important for things like the personal robots, self-driving cars, and autonomous drones we’re seeing more and more in our daily lives.


Today, Dr. Hua talks about how the latest advances in AI and machine learning are making big improvements on image recognition, video understanding and even the arts. He also explains the distributed ensemble approach to active learning, where humans and machines work together in the lab to get computer vision systems ready to see and interpret the open world.

When we think of medals, we usually picture them over the pocket of a military hero, not over the pocket protector of a computer scientist. That may be because not many academics end up working with the Department of Defense. But Dr. Chris White, now a Principal Researcher at Microsoft Research, has, and he’s received several awards for his efforts in fighting terrorism and crime with big data, statistics and machine learning.


Today, Dr. White talks about his “problem-first” approach to research, explains the vital importance of making data understandable for everyone, and shares the story of how a one-week detour from academia turned into an extended tour in Afghanistan, a stint at DARPA, and, eventually, a career at Microsoft Research.

In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.


Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

With 7 billion people on the planet, you might be surprised to learn that approximately a billion of those people experience some form of disability. Enter Principal Researcher and Research Manager, Dr. Merrie Ringel Morris, and the Ability Group at Microsoft Research. They’re working to remove accessibility barriers both to and through technology, empowering people with disabilities to better perform their daily tasks.


Today, Dr. Morris gives us some fascinating insights into the world of “ability,” talks about how technology is augmenting not only sensory and motor abilities, but cognitive and social abilities as well, and shares how Microsoft, through its AI for Accessibility initiative, is committed to extending the capabilities and enhancing the quality of life for every person on the planet.


 

Humans are wired to communicate, but we don’t always understand each other. Especially when we don’t speak the same language. But Arul Menezes, the Partner Research Manager who heads MSR’s Machine Translation team, is working to remove language barriers to help people communicate better. And with the help of some innovative machine learning techniques, and the combined brainpower of machine translation, natural language and machine learning teams in Redmond and Beijing, it’s happening sooner than anyone expected.


Today, Menezes talks about how the advent of deep learning has enabled exciting advances in machine translation, including applications for people with disabilities, and gives us an inside look at the recent “human parity” milestone at Microsoft Research, where machines translated a news dataset from Chinese to English with the same accuracy and quality as a person.

Some of the world’s leading architects are people that you’ve probably never heard of, and they’ve designed and built some of the world’s most amazing structures that you’ve probably never seen. Or at least you don’t think you have. One of these architects is Dr. Doug Burger, Distinguished Engineer at Microsoft Research NExT. And, if you use a computer, or store anything in the Cloud, you’re a beneficiary of the beautiful architecture that he, and people like him, work on every day.


Today, in a fast-paced interview, Dr. Burger talks about how advances in AI and deep machine learning have placed new acceleration demands on current hardware and computer architecture, offers some observations about the demise of Moore’s Law, and shares his vision of what life might look like in a post-CPU, post-von-Neumann computing world.

Autonomous flying agents – or flying robots – may seem like the stuff of sci-fi to the average person, but to Dr. Ashish Kapoor, Principal Researcher and Research Manager of the Aerial Informatics and Robotics Group at Microsoft Research, they’re much closer to science than to fiction. And, having built – and flight tested – his own airplane, complete with state-of-the-art avionics designed to run AI and ML algorithms, he has the street cred – or should we say flight cred – to prove it.


Today, Dr. Kapoor talks about how cutting-edge machine learning techniques are empowering a new generation of autonomous vehicles, and tells us all about AirSim, an innovative platform that’s helping bridge the simulator-to-reality gap, paving the way for safer, more robust real-world AI systems of all kinds

Teaching computers to read, think and communicate like humans is a daunting task, but it’s one that Dr. Geoff Gordon embraces with enthusiasm and optimism. Moving from an academic role at Carnegie Mellon University, to a new role as Research Director of the Microsoft Research Lab in Montreal, Dr. Gordon embodies the current trend toward the partnership between academia and industry as we enter what many believe will be a new era of progress in machine learning and artificial intelligence.


Today, Dr. Gordon gives us a brief history of AI, including his assessment of why we might see a break in the weather-pattern of AI winters, talks about how collaboration is essential to innovation in machine learning, shares his vision of the mindset it takes to tackle the biggest questions in AI, and reveals his life-long quest to make computers less… well, less computer-like.

Emotions are fundamental to human interaction, but in a world where humans are increasingly interacting with AI systems, Dr. Mary Czerwinski, Principal Researcher and Research Manager of the Visualization and Interaction for Business and Entertainment group at Microsoft Research, believes emotions may be fundamental to our interactions with machines as well. And through her team’s work in affective computing, the quest to bring Artificial Emotional Intelligence – or AEI – to our computers may be closer than we think.


Today, Dr. Czerwinski tells us how a cognitive psychologist found her way into the research division of the world’s largest software company, suggests that rather than trying to be productive 24/7, we should aim for Emotional Homeostasis instead, and tells us how, if we do it right, our machines could become a sort of “emotional at-work DJ,” sensing and responding to our emotional states, and helping us to become happier and more productive at the same time.

From ancient hieroglyphics to secret decoder rings to World War II Enigma code-makers and code-breakers, cryptography has always held a particular fascination for us. But few of us have the skills – or can actually do the math – to unlock the mysteries of encrypted data. Fortunately, Dr. Kristin Lauter, distinguished mathematician, founder of the Women in Numbers Network, and Principal Researcher and Research Manager for the Cryptography Group at Microsoft Research, can. And she is using her powers for good, not for evil!


Today, Dr. Lauter tells us why she feels lucky  to do math for a living, explains the singular beauty of elliptic curves and the singular difficulty of supersingular isogeny graphs, talks about how homomorphic encryption – part of the field of Private AI – allows us to operate on, while still protecting, our most sensitive data, and shares her dream of one day, seeing a Grace Hopper-like conference to celebrate women in mathematics.

When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming.


Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your Wi-Fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions.


Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.

Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.


Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.


 

 


There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it.


Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.


 


Artificial intelligence has captured our imagination and made many things we would have thought impossible only a few years ago seem commonplace today. But AI has also raised some challenging issues for society writ large. Enter Dr. Kate Crawford, a principal researcher at the New York City lab of Microsoft Research. Dr. Crawford, along with an illustrious group of colleagues in computer science, engineering, social science, business and law, has dedicated her research to addressing the social implications of AI, including big topics like bias, labor and automation, rights and liberties, and ethics and governance.


Today, Dr. Crawford talks about both the promises and the problems of AI; why— when it comes to data – bigger isn’t necessarily better; and how – even in an era of increasingly complex technological advances – we can adopt AI design principles that empower people to shape their technical tools in ways they’d like to use them most.


 


With all the sensational headlines about artificial intelligence, it’s reassuring to know that some of the world’s most brilliant minds are developing AI systems for entirely practical reasons. One of those minds belongs to Dr. Antonio Criminisi, a Principal Researcher at Microsoft Research in Cambridge, England. And one of those reasons is to help medical professionals provide better healthcare to their patients.Today, Dr. Criminisi talks about Project InnerEye, an innovative machine learning tool that helps radiologists identify and analyze 3-D images of cancerous tumors. He also gives us some insight into his work on deep neural decision forests and tells us how gaming algorithms made their way into medical technology, moving from gamer to patient, and turning outside-in imaging… inside-out.


 


 


If you’ve ever wondered if you could find the perfect combination of computer scientist… and Macgyver, look no further than Dr. Peli de Halleux, principal Research Software Design Engineer at Microsoft Research. A key member of the MSR RiSE team, Peli is part of the MakeCode initiative that brings physical computing to classrooms around the country and around the world. Today, Peli talks about the Maker Movement in K-12 education, the hard work that goes on behind the scenes to deliver a “seamless” user experience for both kids and teachers, and how to get children excited about coding through hands on experience in early computer science education.


Big data is a big deal, and if you follow the popular technical press, you’ll have heard all the metaphors: data is the new oil, the new bacon, the new currency, the new electricity. It’s even been called the new black. While data may not actually be any of these things, we can say this: in today’s networked world, data is increasingly valuable and it is essential to research, both basic and applied.


Today, we welcome a special guest to the podcast. Dr. Igor Perisic is the Vice President of Engineering and Chief Data Officer at LinkedIn, the social network for business and employment. Today, Dr. Perisic talks about the key attributes of a data scientist, how AI and machine learning are helping personalize member experiences, why we should all be big open source fans, and how LinkedIn is partnering with other researchers through their innovative Economic Graph program to create economic opportunity for every member of the global workforce.


All this and much more on this episode of the Microsoft Research Podcast.

Every day, computers take on more and more of our daily tasks. Fill in a few cells on your spreadsheet? It’ll fill in the rest. Ask your car for directions? It’ll get you there. Anymore, we can program computers to do almost anything. But what about programming computers to… program computers? That’s a task that Dr. Rishabh Singh, and the team in the Cognition group at Microsoft Research, are tackling with Neural Program Synthesis, also known as artificial programming.


Today, Dr. Singh explains how deep neural networks are already training computers to do things like take classes and grade assignments, shares how programmers can perform complicated, high-level debugging through the delightfully named process of neural fuzzing, and lays out his vision to democratize computer programming in the brave new world of Software 2.0.


 


As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.


Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”


 


If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC - group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality.


Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.


 


When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.


 


 


 


Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.


In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is a… programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

In a wide-ranging interview, veteran Microsoft Researcher, Dr. Steven Drucker talks about his work in data visualization, the importance of clear communication in a world of complex algorithms and big data, and the long, slow work of big breakthroughs. He also offers some pro-tips to aspiring researchers, and tells us why stand-up comedy is an important skill for computer scientists.

On today’s episode, neuroscientist and virtual reality researcher, Dr. Mar Gonzalez Franco, talks about her work in VR, explains how avatars can help increase our empathy and reduce our biases via role play, and addresses the misconceptions that exist between the immersive experiences of virtual reality and psychedelic drugs.

If you’ve ever watched King of Kong: Fistful of Quarters, you know what a big deal it is to beat a video arcade game that was designed not to lose. Most humans can’t even come close. Enter Harm van Seijen, and a team of machine learning researchers from Microsoft Maluuba in Montreal. They took on Ms. Pac-man. And won. Today we’ll talk to Harm about his work in reinforcement learning, the inspiration for hybrid reward architecture, visit a few islands of tractability and get an inside look at the science behind the AI defeat of one of the most difficult video arcade games around.

When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Today, Dr. Horvitz talks about the goal of artificial intelligence, his vision for our collaborative future with machines, what we can learn from the Wright brothers, and how a short stint of “six months, maximum” became an illustrious and, in his words, joyful, 25-year career at Microsoft Research.

Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.

Dr. Eyal Ofek is a senior researcher at Microsoft Research and his work deals mainly with, well, reality. Augmented and virtual reality, to be precise. A serial entrepreneur before he came to MSR, Dr. Ofek knows a lot about the “long nose of innovation” and what it takes to bring a revolutionary new technology to a world that’s ready for it.


On today’s podcast, Dr. Ofek talks about the unique challenges and opportunities of augmented and virtual reality from both a technical and social perspective; tells us why he believes AR and VR have the potential to be truly revolutionary, particularly for people with disabilities; explains why, while we’re doing pretty well in the virtual worlds of sight and sound, our sense of virtual touch remains a bit more elusive; and reveals how, if he and his colleagues are wildly successful, it won’t be that long before we’re living in a whole new world of extension, expansion, enhancement and equality.https://www.microsoft.com/research

Dr. Susan Dumais knows you have things to do, and if you need help finding stuff to get them done (and you probably do) then her long and illustrious career in search technologies has been worth it. Situated firmly in Louis Pasteur’s quadrant of the research grid (the square where you answer “yes” to both the quest for fundamental understanding and use-based applications) the Microsoft Technical Fellow, and Deputy Lab Director of MSR AI, has made finding information the focus of her career, and has probably made your life a little more productive in the process.


Today, Dr. Dumais tells us how the landscape of information retrieval has evolved over the past twenty years; reminds us that queries don’t fall from the sky but are grounded in the context of real people, real events and real time; talks about her current interest in non-web-based search (or how I can easily put my hands on my own digital belongings) and reveals what apples and Michael Jordan have in common with search research.https://www.microsoft.com/research

In 2018, Microsoft launched the Microsoft AI Residency Program, a year-long, expanded research experience designed to give recent graduates in a variety of fields the opportunity to work alongside prominent researchers at MSR on cutting edge AI technologies to solve real-world problems. Dr. Brian Broll was one of them. A newly minted PhD in Computer Science from Vanderbilt University, Dr. Broll was among the inaugural cohort of AI residents who spent a year working on machine learning in game environments and is on the pod to talk about it!


Today, Dr. Broll gives us an overview of the work he did and the experience he had as a Microsoft AI Resident, talks about his passion for making complex concepts easier and more accessible to novices and young learners, and tells us how growing up on a dairy farm in rural Minnesota helped prepare him for a life in computer science solving some of the toughest problems in AI.


 


https://www.microsoft.com/research

Dr. Ed Cutrell is a Principal Researcher in the Ability group at Microsoft Research and he’s convinced that great technology should be available to everyone. Working in the fields of Accessibility and Information and Communication Technologies for Development (aka ICT4D), his research has explored computing solutions for people across the resource and ability spectrum, both here and around the world.


Today, Dr. Cutrell gives us an overview of his work in the disability and inclusive design space, explains the vital importance of interdisciplinarity – a fancy way of saying many ways of thinking and many ways of knowing – and tells us how a dumb phone beat a smart tablet in rural India… and what that meant to researchers.


https://www.microsoft.com/research


 

As computing moves to the cloud, there is an increasing need for privacy in AI. In an ideal world, users would have the ability to compute on encrypted data without sacrificing performance. Enter Dr. Olli Saarikivi, a post-doctoral researcher in the RiSE group at MSR. He, along with a stellar group of cross-disciplinary colleagues, are bridging the gap with CHET, a compiler and runtime for homomorphic evaluation of tensor programs, that keeps data private while making the complexities of homomorphic encryption schemes opaque to users.


On today’s podcast, Dr. Saarikivi tells us all about CHET, gives us an overview of some of his other projects, including Parasail, a novel approach to parallelizing seemingly sequential applications, and tells us how a series of unconventional educational experiences shaped his view of himself, and his career as a researcher. https://www.microsoft.com/research

The ability to read and understand unstructured text, and then answer questions about it, is a common skill among literate humans. But for machines? Not so much. At least not yet! And not if Dr. T.J. Hazen, Senior Principal Research Manager in the Engineering and Applied Research group at MSR Montreal, has a say. He’s spent much of his career working on machine speech and language understanding, and particularly, of late, machine reading comprehension, or MRC.


On today’s podcast, Dr. Hazen talks about why reading comprehension is so hard for machines, gives us an inside look at the technical approaches applied researchers and their engineering colleagues are using to tackle the problem, and shares the story of how an a-ha moment with a Rubik’s Cube inspired a career in computer science and a quest to teach computers to answer complex, text-based questions in the real world.


https://microsoft.com/research

In an era of unprecedented advances in AI and machine learning, current gen systems and networks are being challenged by an unprecedented level of complexity and cost. Fortunately, Dr. Ganesh Ananthanarayanan, a researcher in the Mobility and Networking group at MSR, is up for a challenge. And, it seems, the more computationally intractable the better! A prolific researcher who’s interested in all aspects of systems and networking, he’s on a particular quest to extract value from live video feeds and develop “killer apps” that will have a practical impact on the world.


Today, Dr. Ananthanarayanan tells us all about Video Analytics for Vision Zero (an award-winning “killer app” that aims to reduce traffic-related fatalities to zero), gives us a wide-angle view of his work in geo-distributed data analytics and client-cloud networking, and explains how the duration and difficulty of a Test Cricket match provides an invaluable lesson for success in life and research.


https://www.microsoft.com/research

Dr. Nathalie Riche envisions a future in which all of our data will be accessible, meaningful, compelling and artistic. And as a researcher in human computer interaction and information visualization at Microsoft Research, she’s working on technical tools that will help us wrangle our data, extract knowledge from it, and communicate with it in a memorable, persuasive and aesthetically pleasing way. In other words, she wants our data to be both smart… and beautiful!


Today, Dr. Riche shares her passion for the art of data driven storytelling, reveals the two superpowers of data visualization, gives us an inside look at some innovative projects designed to help us th(ink) with digital ink, and tells the story of how a young woman with an artist’s heart headed into computer science, took a detour to the beach, paid for it with research and ended up with a rewarding career that brings both art and computing together.


https://www.microsoft.com/research


 

This episode first aired in January, 2018. When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.


https://www.microsoft.com/research

This episode first aired in March, 2018. There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it.Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.


https://www.microsoft.com/research

Dr. Johannes Gehrke is a Microsoft Technical Fellow and head of Architecture and Machine Learning for the Intelligent Communications and Conversations Cloud in Microsoft’s Experiences and Devices division. But lest you think his lofty position makes him in any way superior to you, let me tell you, he knows who works for whom, and he’ll be the first to tell you that you are his boss!


On today’s podcast, Dr. Gehrke frames the new, cloud-powered work world as a fast paced, widely-distributed workplace that demands real-time decision-making and collaboration – and explains how products like Microsoft Teams are meeting those demands – and tells us, both directly and indirectly, about the future of work, which for Microsoft, involves a pivot from an app-centric approach to a people-centric approach where, by using an AI-infused productivity suite coupled with the power of the cloud, we can essentially “hire Microsoft” to help us get our work done.

This episode first aired in November, 2017 - Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counterintuitive.Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of 4 young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks – could help us be more productive, and experience a better quality of life at the same time.https://microsoft.com/research

This episode first aired in January, 2018. As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”


https://www.microsoft.com/research

If you’re like me, you’re no longer amazed by how all your technologies can work for you. Rather, you’ve begun to take for granted that they simply should work for you. Instantly. All together. All the time. The fact that you’re not amazed is a testimony to the work that people like Dr. Lidong Zhou, Assistant Managing Director of Microsoft Research Asia, do every day. He oversees some of the cutting-edge systems and networking research that goes on behind the scenes to make sure you’re not amazed when your technologies work together seamlessly but rather, can continue to take it for granted that they will!


Today, Dr. Zhou talks about systems and networking research in an era of unprecedented systems complexity and what happens when old assumptions don’t apply to new systems, explains how projects like CloudBrain are taking aim at real-time troubleshooting to address cloud-scale, network-related problems like “gray failure,” and tells us why he believes now is the most exciting time to be a systems and networking researcher.

Dr. Chris Bishop is a Microsoft Technical Fellow and director of MSR Cambridge, where he oversees an impressive portfolio of research including machine learning, AI, healthcare and gaming. Phil Spencer is the Executive Vice President of Gaming at Microsoft where he oversees everything from the design of the next Xbox console to the creation and release of blockbuster properties like Halo, Gears of War and Forza Motorsport. These two powerhouse executives are pushing the boundaries of creativity, technical innovation and fun across the spectrum of gaming genres and devices for nearly 2 billion gamers around the world.


On today’s podcast, Chris and Phil discuss their respective roles in Microsoft’s gaming ecosystem, revealing a sort of “enrichment pipeline” that flows all the way from researcher to developer to gamer. They also give us an inside look at the close collaboration between the world-class research organization of MSR and the world-class gaming franchise of Xbox, highlighting Microsoft’s unique ability to deliver the tools, talent and resources that fuel innovation and help shape the future of gaming.http://www.microsoft.com/research

You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.


On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.

If you’ve recently found it more difficult to focus your attention for a lengthy stretch of time in order to get a complex task done… or worse, found it difficult even to find a lengthy stretch of time in which to try, you’re not alone. And actually, you’re in luck. Dr. Shamsi Iqbal, a senior researcher in the Information and Data Sciences group at Microsoft Research, wants to help you manage your attention better and be more productive at the same time. And she’s using technology to do it!


On today’s podcast, Dr. Iqbal tells us about her work in the field of micro-productivity, a line of research that takes aim at the short spurts of time she calls micro-moments that we otherwise might have considered too short to get anything useful done. She also explains why distraction can be good for us and gives us some advice on how to make the most of our cognitive resources, whether by setting aside time to tackle big tasks in the traditional way or by breaking them down into micro-tasks… and “outsourcing” them to ourselves!

If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.


On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

When was the last time you had a meaningful conversation with your computer… and felt like it truly understood you? Well, if Dr. Xuedong Huang, a Microsoft Technical Fellow and head of Microsoft’s Speech and Language group, is successful, you will. And if his track record holds true, it’ll be sooner than you think!


On today’s podcast, Dr. Huang talks about his role as Microsoft’s Chief Speech Scientist, gives us some inside details on the latest milestones in speech and language technology, and explains how mastering speech recognition, translation and conversation will move machines further along the path from “perceptive AI” to “cognitive AI” and that much closer to truly human intelligence.

Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.


Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

If you want to know what’s going on in the world of human computer interaction research, or what’s new at the CHI Conference on Human Factors in Computing Systems, you should hang out with Dr. Ken Hinckley, a principal researcher and research manager in the EPIC group at Microsoft Research, and Dr. Merrie Ringel Morris, a principal researcher and research manager in the Ability group. Both are prolific HCI researchers who are seeking, from different angles, to augment the capability of technologies and improve the experiences people have with them.


On today’s podcast, we get to hang out with both Dr. Hinckley and Dr. Morris as they talk about life at the intersection of hardware, software and human potential, discuss how computers can enhance human lives, especially in some of the most marginalized populations, and share their unique approaches to designing and building technologies that really work for people and for society.

In the world of relational databases, structured query language, or SQL, has long been King of the Queries, primarily because of its ubiquity and unparalleled performance. But many users prefer a mix of imperative programming, along with declarative SQL, because its user-defined functions (or UDFs) allow for good software engineering practices like modularity, readability and re-usability. Sadly, these benefits have traditionally come with a huge performance penalty, rendering them impractical in most situations. That bothered Dr. Karthik Ramachandra, a Senior Applied Scientist at Microsoft Research India, so he’s spent a great deal of his career working on improving an imperative complement to SQL in database systems.


Today, Dr. Ramachandra gives us an overview of the historic trade-offs between declarative and imperative programming paradigms, tells us some fantastic stories, including The Tale of Two Engineers and The UDF Story, Parts 1 and 2, and introduces us to Froid – that’s F-R-O-I-D, not the Austrian psychoanalyst – which is an extensible, language-agnostic framework for optimizing imperative functions in databases, offering the benefits of UDFs without sacrificing performance.

We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.


Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

 


Dr. Marc Pollefeys is a Professor of Computer Science at ETH Zurich, a Partner Director of Science for Microsoft, and the Director of a new Microsoft Mixed Reality and AI lab in Switzerland. He’s a leader in the field of computer vision research, but it’s hard to pin down whether his work is really about the future of computer vision, or about a vision of future computers. Arguably, it’s both!


On today’s podcast, Dr. Pollefeys brings us up to speed on the latest in computer vision research, including his innovative work with Azure Spatial Anchors, tells us how devices like Kinect and HoloLens may have cut their teeth in gaming, but turned out to be game changers for both research and industrial applications, and explains how, while it’s still early days now, in the future, you’re much more likely to put your computer on your head than on your desk or your lap.

Ann Paradiso is an interaction designer and the Principal User Experience Designer for the NExT Enable group at Microsoft Research. She’s also the epitome of a phrase she often uses to describe other people: a force of nature. Together with a diverse array of team members and collaborators, many of whom have ALS or other conditions that affect mobility and speech, Ann works on new interaction paradigms for assistive technologies hoping to make a more bespoke approach to technology solutions accessible, at scale, to the people who need it most.


On today’s podcast, Ann tells us all about life in the extreme constraint design lane, explains what a PALS is, and tells us some incredibly entertaining stories about how the eye tracking technology behind the Eye Controlled Wheelchair and the Hands-Free Music Project has made its way from Microsoft’s campus to some surprising events around the country, including South by Southwest and Mardi Gras.

This episode first aired in September, 2018:


You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, Massachusetts, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.


On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning – now a feature of Azure Machine Learning – that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

If you’ve ever played video games, you know that for the most part, they look a lot better than they sound. That’s largely due to the fact that audible sound waves are much longer – and a lot more crafty – than visual light waves, and therefore, much more difficult to replicate in simulated environments. But Dr. Nikunj Raghuvanshi, a Senior Researcher in the Interactive Media Group at Microsoft Research, is working to change that by bringing the quality of game audio up to speed with the quality of game video. He wants you to hear how sound really travels – in rooms, around corners, behind walls, out doors – and he’s using computational physics to do it.


Today, Dr. Raghuvanshi talks about the unique challenges of simulating realistic sound on a budget (both money and CPU), explains how classic ideas in concert hall acoustics need a fresh take for complex games like Gears of War, reveals the computational secret sauce you need to deliver the right sound at the right time, and tells us about Project Triton, an acoustic system that models how real sound waves behave in 3-D game environments to makes us believe with our ears as well as our eyes.

When we think of information processing systems, we often think of computers, but we ourselves are made up of information processing systems – trillions of them – also known as the cells in our bodies. While these cells are robust, they’re also extraordinarily complex and not altogether predictable. Wouldn’t it be great, asks Dr. Andrew Phillips, head of the Biological Computation Group at Microsoft Research in Cambridge, if we could figure out exactly how these building blocks of life work and harness their power with the rigor and predictability of computer science? To answer that, he’s spent a good portion of his career working to develop a system of intelligence that can, literally, program biology.


Today, Dr. Phillips talks about the challenges and rewards inherent in reverse engineering biological systems to see how they perform information processing. He also explains what we can learn from stressed out bacteria, and tells us about Station B, a new end-to-end platform his team is working on that aims to reduce the trial and error nature of lab experiments and help scientists turn biological cells into super-factories that could solve some of the most challenging problems in medicine, agriculture, the environment and more.

This episode first aired in August of 2018.


You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.


 

If you’ve ever wondered why, in the age of the internet, we still don’t hold our elections online, you need to spend more time with Dr. Josh Benaloh, Senior Cryptographer at Microsoft Research in Redmond. Josh knows a lot about elections, and even more about homomorphic encryption, the mathematical foundation behind the end-to-end verifiable election systems that can dramatically improve election integrity today and perhaps move us toward wide-scale online voting in the future.


Today, Dr. Benaloh gives us a brief but fascinating history of elections, explains how the trade-offs among privacy, security and verifiability make the relatively easy math of elections such a hard problem for the internet, and tells the story of how the University of Michigan fight song forced the cancellation of an internet voting pilot.

Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you’d talk to another person. That’s the easy part. The hard part is getting your machine to understand and talk back to you like it’s that other person.


Today, Dr. El Asri talks about the particular challenges she and other scientists face in building sophisticated dialogue systems that lay the foundation for talking machines. She also explains how reinforcement learning, in the form of a text game generator called TextWorld, is helping us get there, and relates a fascinating story from more than fifty years ago that reveals some of the safeguards necessary to ensure that when we design machines specifically to pass the Turing test, we design them in an ethical and responsible way.

If every question in life could be answered by choosing from just a few options, machine learning would be pretty simple, and life for machine learning researchers would be pretty sweet. Unfortunately, in both life and machine learning, things are a bit more complicated. That’s why Dr. Manik Varma, Principal Researcher at MSR India, is developing extreme classification systems to answer multiple-choice questions that have millions of possible options and help people find what they are looking for online more quickly, more accurately and less expensively.


On today’s podcast, Dr. Varma tells us all about extreme classification (including where in the world you might actually run into 10 or 100 million options), reveals how his Parabel and Slice algorithms are making high quality recommendations in milliseconds, and proves, with both his life and his work, that being blind need not be a barrier to extreme accomplishment.

Haiyan Zhang is a designer, technologist and maker of things (really cool technical things) who currently holds the unusual title of Innovation Director at the Microsoft Research lab in Cambridge, England. There, she applies her unusual skillset to a wide range of unusual solutions to real-life problems, many of which draw on novel applications of gaming technology in serious areas like healthcare.


On today’s podcast, Haiyan talks about her unique “brain hack” approach to the human-centered design process, and discusses a wide range of projects, from the connected play experience of Zanzibar, to Fizzyo, which turns laborious breathing exercises for children with cystic fibrosis into a video game, to Project Emma, an application of haptic vibration technology that, somewhat curiously, offsets the effects of tremors caused by Parkinson’s disease.

From his deep technical roots as a principal researcher and founder of the Communications, Collaboration and Signal Processing group at MSR, through his tenure as Managing Director of the lab in Redmond, to his current role as Distinguished Engineer, Chief Scientist for Microsoft Research and manager of the MSR NExT Enable group, Dr. Rico Malvar has seen – and pretty well done – it all.


Today, Dr. Malvar recalls his early years at a fledgling Microsoft Research, talks about the exciting work he oversees now, explains why designing with the user is as important as designing for the user, and tells us how a challenge from an ex-football player with ALS led to a prize winning hackathon project and produced the core technology that allows you to type on a keyboard without your hands and drive a wheelchair with your eyes.

You never know how an incident in your own life might inspire a breakthrough in science, but Dr. Cecily Morrison, a researcher in the Human Computer Interaction group at Microsoft Research Cambridge, can attest to how even unexpected events can cause us to see things through a different – more inclusive – lens and, ultimately, give rise to innovations in research that impact everyone.


On today’s podcast, Dr. Morrison gives us an overview of what she calls the “pillars” of inclusive design, shares how her research is positively impacting people with health issues and disabilities, and tells us how having a child born with blindness put her in touch with a community of people she would otherwise never have met, and on the path to developing Project Torino, an inclusive physical programming language for children with visual impairments.

The entertainment industry has long offered us a vision of the perfect personal assistant: one that not only meets our stated needs but anticipates needs we didn’t even know we had. But these uber-assistants, from the preternaturally prescient Radar O’Reilly in the TV show M.A.S.H. to Tony Stark’s digital know-and-do-it-all Jarvis in Iron Man, have always lived in the realm of fiction or science fiction. That could all change, if Dr. Paul Bennett, Principal Researcher and Research Manager of the Information and Data Sciences group at Microsoft Research, has anything to say about it. He and his team are working to make machines “calendar and email aware,” moving intelligent assistance into the realm of science and onto your workstation.


Today, Dr. Bennett brings us up to speed on the science of contextually intelligent assistants, explains how what we think our machines can do actually shapes what we expect them to do, and shares how current research in machine learning and data science is helping machines reason on our behalf in the quest to help us find the right information effortlessly.

When people first started making software, computers were relatively rare and there was no internet, so programming languages were designed to get the job done quickly and run efficiently, with little thought for security. But software is everywhere now, from our desktops to our cars, from the cloud to the internet of things. That’s why Dr. Jonathan Protzenko, a researcher in the RiSE – or Research in Software Engineering – group at Microsoft Research, is working on designing better software tools in order to make our growing software ecosystem safer and more secure.


Today, Dr. Protzenko talks about what’s wrong with software (and why it’s vitally important to get it right), explains why there are so many programming languages (and tells us about a few he’s been working on), and finally, acts as our digital Sherpa for Project Everest, an assault on software integrity and confidentiality that aims to build and deploy a verified HTTPS stack.

The episode first aired in May, 2018.In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

This episode first aired in January, 2018.When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.


Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.

This episode first aired in March, 2018.Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.

Amos Miller is a product strategist on the Microsoft Research NeXT Enable team, and he’s played a pivotal role in bringing some of MSR’s most innovative research to users with disabilities. He also happens to be blind, so he can appreciate, perhaps in ways others can’t, the value of the technologies he works on, like Soundscape, an app which enhances mobility independence through audio and sound.


On today’s podcast, Amos Miller answers burning questions like how do you make a microwave accessible, what’s the cocktail party effect, and how do you hear a landmark? He also talks about how researchers are exploring the untapped potential of 3D audio in virtual and augmented reality applications, and explains how, in the end, his work is not so much about making technology more accessible, but using technology to make life more accessible.

Dr. Sebastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.


Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.

Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.


Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.

This episode first aired in March (2018)One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions.


Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.


 

After decades of research in processing audio signals, we’ve reached the point of so-called performance saturation. But recent advances in machine learning and signal processing algorithms have paved the way for a revolution in speech recognition technology and audio signal processing. Dr. Ivan Tashev, a Partner Software Architect in the Audio and Acoustics Group at Microsoft Research, is no small part of the revolution, having both published papers and shipped products at the forefront of the science of sound.


On today’s podcast, Dr. Tashev gives us an overview of the quest for better sound processing and speech enhancement, tells us about the latest innovations in 3D audio, and explains why the research behind audio processing technology is, thanks to variations in human perception, equal parts science, art and craft.

In 1998, Microsoft Research opened a small lab in Beijing to expand its research efforts and draw on the immense high-tech talent pool in China. No one expected that only twenty years later, MSR Asia would become the dynamic organization it is today, with innovative research contributing to nearly every part of Microsoft’s business. Dr. Hsiao-Wuen Hon has watched it grow from the beginning and this year, celebrates the lab’s 20th anniversary as Managing Director, Corporate Vice President and Chairman of Microsoft’s Asia-Pacific R&D Group.


On today’s podcast, Dr. Hon gives us a brief history of MSR Asia, from its humble beginnings to its significant role in the AI boom today, talks about MSR Asia’s unique talent pipeline, shares his vision for the complementary roles of machine intelligence and human wisdom, and explains why, he believes, the more progress we make in AI, the better we understand ourselves.

As traditional semiconductor technologies for computer storage scale down, everyone is looking for alternative solutions to the growing gap between the amount of data we’re capable of producing and the amount of data we’re capable of storing. While some have focused on hardware accelerators for machine learning, and others are investigating new memory technologies, Dr. Karin Strauss, a Senior Researcher at Microsoft Research in Redmond, has been exploring the role of biotechnology in IT via an end-to-end system that stores digital data in DNA.


On today’s podcast, Dr. Strauss talks about life at the intersection of computer science and biology which, for many, is more like the intersection of science fiction and science, and explains how the unique properties of DNA could eventually enable us to store really big data in really small places for a really long time.

 


The ancient Chinese philosopher Confucius famously exhorted his pupils to study the past if they would divine the future. In 2018, we get the same advice from a decidedly more modern, but equally philosophical Bill Buxton, Principal Researcher in the HCI group at Microsoft Research. In addition to his pioneering work in computer science and design, Bill Buxton has spent the past several decades amassing a collection of more than a thousand artifacts that chronicle the history of human computer interaction for the very purpose of informing the future of human computer interaction.


Today, in a wide-ranging interview, Bill Buxton explains why Marcel Proust and TS Eliot can be instructive for computer scientists, why the long nose of innovation is essential to success in technology design, why problem-setting is more important than problem-solving, and why we must remember, as we design our technologies, that every technological decision we make is an ethical decision as well.

2018 marks the 10th anniversary of Microsoft Research New England in Cambridge, Massachusetts, so it’s the perfect time to talk with someone who was there from the lab’s beginning: Technical Fellow, Managing Director and Co-founder, Dr. Jennifer Chayes. But not only does Dr. Chayes run the New England lab of MSR, she also directs two other highly renowned, interdisciplinary research labs in New York City and Montreal, Quebec. Add to that a full slate of personal research projects and service on numerous boards, committees and foundations, and you’ve got one of the busiest and most influential women in high tech.


On today’s podcast, Dr. Chayes shares her passion for the value of undirected inquiry, talks about her unlikely journey from rebel to researcher, and explains how she believes her research philosophy – more botanist than boss – prepares the fertile ground necessary for important, innovative and impactful research.

Asta Roseway has a formal title. It’s Principal Research Designer in the HCI group at Microsoft Research. But she’s also been described as a conductor, an alchemist, a millennial in a Gen-Xer’s body and, in her own words, a fusionist. What’s a fusionist, you might ask? Well, you’re about to find out.


On today’s podcast, Asta gives an inside look at one of the most unconventional labs at Microsoft Research. Located at the intersection of science, technology and art, it’s a lab that insists that technology, like art, should push boundaries, tell stories and feed our souls. Get ready for the unexpected because when Asta asks “what if?” you’re likely to find yourself immersed in a world of responsive clothing, smart tattoos, talking plants and even environmentally sensitive… makeup!

You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, MA, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.


On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning - now a feature of Azure Machine Learning - that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

At the heart of any vibrant research community, you’ll find a diverse range of scientists. You’re also likely to find a robust internship program, like the one at Microsoft Research. This summer, MSR welcomed another stellar group of interns who had the opportunity to learn, collaborate, and network with colleagues and mentors who will impact their lives for years to come.


On today’s podcast, you’ll hear the stories of three of these interns, each of whom came to Microsoft Research from a different field, with a different story and a different perspective, but all of whom share MSR’s passion for finding innovative solutions to the world’s toughest challenges.

Dr. Nancy Baym is a communication scholar, a Principal Researcher in MSR’s Cambridge, Massachusetts, lab, and something of a cyberculture maven. She’s spent nearly three decades studying how people use communication technologies in their everyday relationships and written several books on the subject. The big take away? Communication technologies may have changed drastically over the years, but human communication itself? Not so much.


Today, Dr. Baym shares her insights on a host of topics ranging from the arduous maintenance requirements of social media, to the dialectic tension between connection and privacy, to the funhouse mirror nature of emerging technologies. She also talks about her new book, Playing to the Crowd: Musicians, Audiences and the Intimate Work of Connection, which explores how the internet transformed – for better and worse – the relationship between artists and their fans.

Datacenters have a hard time keeping their cool. Literally. And with more and more datacenters coming online all over the world, calls for innovative solutions to “cool the cloud” are getting loud. So, Ben Cutler and the Special Projects team at Microsoft Research decided to try to beat the heat by using one of the best natural venues for cooling off on the planet: the ocean. That led to Project Natick, Microsoft’s prototype plan to deploy a new class of eco-friendly datacenters, under water, at scale, anywhere in the world, from decision to power-on, in 90 days. Because, presumably for Special Projects, go big or go home.


In today’s podcast we find out a bit about what else the Special Projects team is up to, and then we hear all about Project Natick and how Ben and his team conceived of, and delivered on, a novel idea to deal with the increasing challenges of keeping datacenters cool, safe, green, and, now, dry as well!

The wildly popular video game, Minecraft, might appear to be an unlikely candidate for machine learning research, but to Dr. Katja Hofmann, the research lead of Project Malmo in the Machine Intelligence and Perception Group at Microsoft Research in Cambridge, England, it’s the perfect environment for teaching AI agents, via reinforcement learning, to act intelligently – and cooperatively – in the open world.


Today, Dr. Hofmann talks about her vision of a future where machines learn to collaborate with people and empower them to help solve complex, real-world problems. She also shares the story of how her early years in East Germany, behind the Iron Curtain, shaped her both personally and professionally, and ultimately facilitated a creative, exploratory mindset about computing that informs her work to this day.

You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.


Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.

If your idea of a great job includes pursuing untethered research, shepherding brilliant researchers and helping shape the long-term strategy of one of the largest tech companies in the world… oh, and also publishing prolifically, authoring patents, winning awards and speaking around the world… you are in good company. That’s what Dr. Victor Bahl, Distinguished Scientist and Director of Mobility and Networking at Microsoft Research, does for a living. And he loves it!


Today, in our first live podcast, recorded at MSR’s 2018 Faculty Summit, Dr. Bahl shares some fascinating stories from his long and illustrious career, gives us an inside look at what’s new in networking, and, explains why, in an industry where it pays to be the smartest person in the room, it’s important to be a world-class listener.

Kevin Scott has embraced many roles over the course of his illustrious career in technology: software developer, engineering executive, researcher, angel investor, philanthropist, and now, Chief Technology Officer of Microsoft. But perhaps no role suits him so well – or has so fundamentally shaped all the others – as his self-described role of “all-around geek.”


Today, in a wide-ranging interview, Kevin shares his insights on both the history and the future of computing, talks about how his impulse to celebrate the extraordinary people “behind the tech” led to an eponymous non-profit organization and a podcast, and… reveals the superpower he got when he was in grad school.

Dr. Lenin Ravindranath Sivalingam is a researcher by trade, but by nature, he’s an entrepreneur, and a hacker with a heart of gold. It’s this combination of skill and passion that informs his work at Microsoft Research, driving him to discover and build tools that will make life both easier for developers and better for end-users.


Today, Dr. Ravindranath Sivalingam tells us why he is so passionate about what he does, explains how internships can literally change your life, and shares the story of how a hackathon idea turned into a prize-winning project… and then became the backbone of a powerhouse tool for gamers and their fans.


To learn more about Dr. Ravindranath Sivalingam, and how Microsoft researchers are working to make life more easier and more robust for everyone, visit Microsoft.com/research

First aired on January 17, 2018. If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC – group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality.Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.

First aired on December 4th, 2017. When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Dr. Horvitz talks about the goal of artificial intelligence, his vision for our collaborative future with machines, what we can learn from the Wright brothers, and how a short stint of “six months, maximum” became an illustrious and, in his words, joyful, 25-year career at Microsoft Research.

This episode first aired in January (2018).In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is… a programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

This episode first aired in April (2018). When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming.Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your wi-fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

Developing complex artificial intelligence systems in a lab is a challenging task, but what happens when they go into production and interact with real humans? That’s what researchers like Dr. Fernando Diaz, a Principal Research Manager at Microsoft Research Montreal, want to know. He and his colleagues are trying to understand – and address – the social implications of these systems as they enter the open world.


Today, Dr. Diaz shares his insights on the kinds of questions we need to be asking about artificial intelligence and its impact on society. He also talks about how algorithms can affect your taste in music, and why now, more than ever, computer science education needs to teach ethics along with algorithms.

This episode first aired in November (2017). Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.

In technical terms, computer vision researchers “build algorithms and systems to automatically analyze imagery and extract knowledge from the visual world.” In layman’s terms, they build machines that can see. And that’s exactly what Principal Researcher and Research Manager, Dr. Gang Hua, and Computer Vision Technology team, are doing. Because being able to see is really important for things like the personal robots, self-driving cars, and autonomous drones we’re seeing more and more in our daily lives.


Today, Dr. Hua talks about how the latest advances in AI and machine learning are making big improvements on image recognition, video understanding and even the arts. He also explains the distributed ensemble approach to active learning, where humans and machines work together in the lab to get computer vision systems ready to see and interpret the open world.

When we think of medals, we usually picture them over the pocket of a military hero, not over the pocket protector of a computer scientist. That may be because not many academics end up working with the Department of Defense. But Dr. Chris White, now a Principal Researcher at Microsoft Research, has, and he’s received several awards for his efforts in fighting terrorism and crime with big data, statistics and machine learning.


Today, Dr. White talks about his “problem-first” approach to research, explains the vital importance of making data understandable for everyone, and shares the story of how a one-week detour from academia turned into an extended tour in Afghanistan, a stint at DARPA, and, eventually, a career at Microsoft Research.

In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.


Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

With 7 billion people on the planet, you might be surprised to learn that approximately a billion of those people experience some form of disability. Enter Principal Researcher and Research Manager, Dr. Merrie Ringel Morris, and the Ability Group at Microsoft Research. They’re working to remove accessibility barriers both to and through technology, empowering people with disabilities to better perform their daily tasks.


Today, Dr. Morris gives us some fascinating insights into the world of “ability,” talks about how technology is augmenting not only sensory and motor abilities, but cognitive and social abilities as well, and shares how Microsoft, through its AI for Accessibility initiative, is committed to extending the capabilities and enhancing the quality of life for every person on the planet.


 

Humans are wired to communicate, but we don’t always understand each other. Especially when we don’t speak the same language. But Arul Menezes, the Partner Research Manager who heads MSR’s Machine Translation team, is working to remove language barriers to help people communicate better. And with the help of some innovative machine learning techniques, and the combined brainpower of machine translation, natural language and machine learning teams in Redmond and Beijing, it’s happening sooner than anyone expected.


Today, Menezes talks about how the advent of deep learning has enabled exciting advances in machine translation, including applications for people with disabilities, and gives us an inside look at the recent “human parity” milestone at Microsoft Research, where machines translated a news dataset from Chinese to English with the same accuracy and quality as a person.

Some of the world’s leading architects are people that you’ve probably never heard of, and they’ve designed and built some of the world’s most amazing structures that you’ve probably never seen. Or at least you don’t think you have. One of these architects is Dr. Doug Burger, Distinguished Engineer at Microsoft Research NExT. And, if you use a computer, or store anything in the Cloud, you’re a beneficiary of the beautiful architecture that he, and people like him, work on every day.


Today, in a fast-paced interview, Dr. Burger talks about how advances in AI and deep machine learning have placed new acceleration demands on current hardware and computer architecture, offers some observations about the demise of Moore’s Law, and shares his vision of what life might look like in a post-CPU, post-von-Neumann computing world.

Autonomous flying agents – or flying robots – may seem like the stuff of sci-fi to the average person, but to Dr. Ashish Kapoor, Principal Researcher and Research Manager of the Aerial Informatics and Robotics Group at Microsoft Research, they’re much closer to science than to fiction. And, having built – and flight tested – his own airplane, complete with state-of-the-art avionics designed to run AI and ML algorithms, he has the street cred – or should we say flight cred – to prove it.


Today, Dr. Kapoor talks about how cutting-edge machine learning techniques are empowering a new generation of autonomous vehicles, and tells us all about AirSim, an innovative platform that’s helping bridge the simulator-to-reality gap, paving the way for safer, more robust real-world AI systems of all kinds

Teaching computers to read, think and communicate like humans is a daunting task, but it’s one that Dr. Geoff Gordon embraces with enthusiasm and optimism. Moving from an academic role at Carnegie Mellon University, to a new role as Research Director of the Microsoft Research Lab in Montreal, Dr. Gordon embodies the current trend toward the partnership between academia and industry as we enter what many believe will be a new era of progress in machine learning and artificial intelligence.


Today, Dr. Gordon gives us a brief history of AI, including his assessment of why we might see a break in the weather-pattern of AI winters, talks about how collaboration is essential to innovation in machine learning, shares his vision of the mindset it takes to tackle the biggest questions in AI, and reveals his life-long quest to make computers less… well, less computer-like.

Emotions are fundamental to human interaction, but in a world where humans are increasingly interacting with AI systems, Dr. Mary Czerwinski, Principal Researcher and Research Manager of the Visualization and Interaction for Business and Entertainment group at Microsoft Research, believes emotions may be fundamental to our interactions with machines as well. And through her team’s work in affective computing, the quest to bring Artificial Emotional Intelligence – or AEI – to our computers may be closer than we think.


Today, Dr. Czerwinski tells us how a cognitive psychologist found her way into the research division of the world’s largest software company, suggests that rather than trying to be productive 24/7, we should aim for Emotional Homeostasis instead, and tells us how, if we do it right, our machines could become a sort of “emotional at-work DJ,” sensing and responding to our emotional states, and helping us to become happier and more productive at the same time.

From ancient hieroglyphics to secret decoder rings to World War II Enigma code-makers and code-breakers, cryptography has always held a particular fascination for us. But few of us have the skills – or can actually do the math – to unlock the mysteries of encrypted data. Fortunately, Dr. Kristin Lauter, distinguished mathematician, founder of the Women in Numbers Network, and Principal Researcher and Research Manager for the Cryptography Group at Microsoft Research, can. And she is using her powers for good, not for evil!


Today, Dr. Lauter tells us why she feels lucky  to do math for a living, explains the singular beauty of elliptic curves and the singular difficulty of supersingular isogeny graphs, talks about how homomorphic encryption – part of the field of Private AI – allows us to operate on, while still protecting, our most sensitive data, and shares her dream of one day, seeing a Grace Hopper-like conference to celebrate women in mathematics.

When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming.


Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your Wi-Fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions.


Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.

Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.


Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.


 

 


There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it.


Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.


 


Artificial intelligence has captured our imagination and made many things we would have thought impossible only a few years ago seem commonplace today. But AI has also raised some challenging issues for society writ large. Enter Dr. Kate Crawford, a principal researcher at the New York City lab of Microsoft Research. Dr. Crawford, along with an illustrious group of colleagues in computer science, engineering, social science, business and law, has dedicated her research to addressing the social implications of AI, including big topics like bias, labor and automation, rights and liberties, and ethics and governance.


Today, Dr. Crawford talks about both the promises and the problems of AI; why— when it comes to data – bigger isn’t necessarily better; and how – even in an era of increasingly complex technological advances – we can adopt AI design principles that empower people to shape their technical tools in ways they’d like to use them most.


 


With all the sensational headlines about artificial intelligence, it’s reassuring to know that some of the world’s most brilliant minds are developing AI systems for entirely practical reasons. One of those minds belongs to Dr. Antonio Criminisi, a Principal Researcher at Microsoft Research in Cambridge, England. And one of those reasons is to help medical professionals provide better healthcare to their patients.Today, Dr. Criminisi talks about Project InnerEye, an innovative machine learning tool that helps radiologists identify and analyze 3-D images of cancerous tumors. He also gives us some insight into his work on deep neural decision forests and tells us how gaming algorithms made their way into medical technology, moving from gamer to patient, and turning outside-in imaging… inside-out.


 


 


If you’ve ever wondered if you could find the perfect combination of computer scientist… and Macgyver, look no further than Dr. Peli de Halleux, principal Research Software Design Engineer at Microsoft Research. A key member of the MSR RiSE team, Peli is part of the MakeCode initiative that brings physical computing to classrooms around the country and around the world. Today, Peli talks about the Maker Movement in K-12 education, the hard work that goes on behind the scenes to deliver a “seamless” user experience for both kids and teachers, and how to get children excited about coding through hands on experience in early computer science education.


Big data is a big deal, and if you follow the popular technical press, you’ll have heard all the metaphors: data is the new oil, the new bacon, the new currency, the new electricity. It’s even been called the new black. While data may not actually be any of these things, we can say this: in today’s networked world, data is increasingly valuable and it is essential to research, both basic and applied.


Today, we welcome a special guest to the podcast. Dr. Igor Perisic is the Vice President of Engineering and Chief Data Officer at LinkedIn, the social network for business and employment. Today, Dr. Perisic talks about the key attributes of a data scientist, how AI and machine learning are helping personalize member experiences, why we should all be big open source fans, and how LinkedIn is partnering with other researchers through their innovative Economic Graph program to create economic opportunity for every member of the global workforce.


All this and much more on this episode of the Microsoft Research Podcast.

Every day, computers take on more and more of our daily tasks. Fill in a few cells on your spreadsheet? It’ll fill in the rest. Ask your car for directions? It’ll get you there. Anymore, we can program computers to do almost anything. But what about programming computers to… program computers? That’s a task that Dr. Rishabh Singh, and the team in the Cognition group at Microsoft Research, are tackling with Neural Program Synthesis, also known as artificial programming.


Today, Dr. Singh explains how deep neural networks are already training computers to do things like take classes and grade assignments, shares how programmers can perform complicated, high-level debugging through the delightfully named process of neural fuzzing, and lays out his vision to democratize computer programming in the brave new world of Software 2.0.


 


As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.


Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”


 


If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC - group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality.


Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.


 


When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.


 


 


 


Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.


In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is a… programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

In a wide-ranging interview, veteran Microsoft Researcher, Dr. Steven Drucker talks about his work in data visualization, the importance of clear communication in a world of complex algorithms and big data, and the long, slow work of big breakthroughs. He also offers some pro-tips to aspiring researchers, and tells us why stand-up comedy is an important skill for computer scientists.

On today’s episode, neuroscientist and virtual reality researcher, Dr. Mar Gonzalez Franco, talks about her work in VR, explains how avatars can help increase our empathy and reduce our biases via role play, and addresses the misconceptions that exist between the immersive experiences of virtual reality and psychedelic drugs.

If you’ve ever watched King of Kong: Fistful of Quarters, you know what a big deal it is to beat a video arcade game that was designed not to lose. Most humans can’t even come close. Enter Harm van Seijen, and a team of machine learning researchers from Microsoft Maluuba in Montreal. They took on Ms. Pac-man. And won. Today we’ll talk to Harm about his work in reinforcement learning, the inspiration for hybrid reward architecture, visit a few islands of tractability and get an inside look at the science behind the AI defeat of one of the most difficult video arcade games around.

When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Today, Dr. Horvitz talks about the goal of artificial intelligence, his vision for our collaborative future with machines, what we can learn from the Wright brothers, and how a short stint of “six months, maximum” became an illustrious and, in his words, joyful, 25-year career at Microsoft Research.

Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.