Microsoft Research Podcast

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.