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Distinguished Lecture Series
2019-2020 Speakers

Rosalind PicardProfessor and Director Media Arts & SciencesMIT

Rosalind Picard

Professor and Director
Media Arts & Sciences

MIT

How Affective Computing can Change our Future Health

October 31, 2019

Abstract:
AI – including machine learning providing emotional intelligence - is becoming embedded in our wearables and smartphones, enabling new insights and interventions for improving lives for many people, including those with Autism, Epilepsy, and Depression. The latter condition, depression, is growing and forecast to become the #1 disease burden by 2030. How close are we to forecasting changes in mood, stress, and physical health before they happen? Could AI help us prevent tomorrow’s worsening mood or ill health, and reduce the likelihood of diseases such as depression, helping people stay healthy instead of becoming sick? This talk will show the latest findings using machine learning and wearable + smartphone sensing, also highlighting ethical and privacy concerns.

Bio:
Rosalind Picard, Sc.D., is founder and director of the Affective Computing Research Group at the MIT Media Laboratory, co-founder of Affectiva, Inc., delivering Emotion AI technology, and co-founder and chief scientist of Empatica, Inc., creators of the first FDA-cleared smart watch used in neurology for detecting seizures. Picard is author of over three hundred peer-reviewed scientific articles in signal processing, computer vision, pattern recognition, machine learning, human-computer interaction, affective computing, and neurology. She is known internationally for her book, Affective Computing, which helped launch the research area by that name. She was a founding member of the IEEE Technical Committee on Wearable Information Systems, helping boot up the field of wearable computing. Picard is a fellow of the IEEE and an elected member of the National Academy of Engineering. She holds a Bachelors in Electrical Engineering from Georgia Tech and Masters and Doctorate degrees in Electrical Engineering and Computer Science from MIT. Picard leads research developing AI/machine learning algorithms, analytics, and sensors for advancing the basic scientific understanding of emotion, stress, and arousal, advancing both basic research and development to improve human health and wellbeing.


Allan BorodinUniversity Professor Computer ScienceUniversity of Toronto

Allan Borodin

University Professor
Computer Science

University of Toronto

What I have Been Doing These Last 50 Years and What I am Doing Now

November 5, 2019

Abstract:
In recognition of my being on the faculty at UT for now 50 years, I was invited to present a DLS. I thank the department for this invitation. And, moreover, I thank the department and the University for providing such a great environment. However, to paraphrase Mark Twain, any rumors of my retirement are exaggerated.

My goal is to briefly review the research topics for which I have made some contributions. These include (n more or less chronological order): Abstract Complexity Theory, Algebraic Complexity Theory, time-space tradeoffs, parallel models of computation and routing, online algorithms, conceptually simple algorithmic paradigms, and more recently, Algorithmic Game Theory/Mechanism Design and Social Choice Theory. Some more general themes in my research are precise models, tradeoffs, positive versus negative results, and more recently, trying to bridge the gap between theory and “practice''.

Bio:
After receiving a PhD from Cornell University, Allan Borodin joined the recently-formed Computer Science Department at the University of Toronto in 1969. He was involved in the growth of the department as it became one of the top ten departments in North America. He served as department chair from 1980 to 1985 and later serves as the acting chair 1992-93. Since then he has continued to be active in the department administration and was one of the main proponents of the very successful MScAC applied research program. He became a University professor in 2011.

Allan Borodin is a Fellow of the Royal Society of Canada, the ACM and the American Association for the Advancement of Science. He was awarded the CRM-Fields-PIMS Prize in 2008. He has been a visiting professor at Cornell University, the University of Washington, the Hebrew University, the Technion, Tel Aviv University, the Weizmann Institute, ETH Zurich, University of Nice, MIT, and the University of Rome.


Barbara J. GroszHiggins Research Professor Natural SciencesHarvard University

Barbara J. Grosz

Higgins Research Professor
Natural Sciences

Harvard University

From Ethical Challenges of Intelligent Systems to Embedding Ethics in Computer Science

December 5, 2019

Abstract:
Computing technologies have become pervasive in daily life, sometimes bringing unintended but harmful consequences. For students to learn to think not only about what technology they could create, but also whether they should create that technology and to recognize the ethical considerations that should constrain their design, computer science curricula must expand to include ethical reasoning about the societal value and impact of these technologies. This talk will describe Harvard's Embedded EthiCS initiative, a novel approach to integrating ethics into computer science education that incorporates ethical reasoning throughout courses in the standard computer science curriculum. It changes existing courses rather than requiring wholly new courses. The talk will begin with a short description of my experiences teaching the course "Intelligent Systems: Design and Ethical Challenges" that inspired the design of Embedded EthiCS. It will then describe the goals behind the design, the way the program works, lessons learned and challenges to sustainable implementations of such a program across different types of academic institutions.

Bio:
Barbara Grosz is Higgins Research Professor of Natural Sciences in the School of Engineering and Applied Sciences at Harvard University and a member of the External Faculty of Santa Fe Institute. She has made groundbreaking contributions to the field of Artificial Intelligence (AI) through her pioneering research in natural language processing and in theories of multi-agent collaboration and their application to human-computer interaction. Her current research explores ways to use models developed in this research to improve health care coordination and science education. She co-founded Harvard's Embedded Ethics program, which integrates teaching of ethical reasoning into core computer science courses. A member of the National Academy of Engineering and the American Philosophical Society, she is a fellow of the American Academy of Arts and Sciences, the Association for the Advancement of Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science, and a corresponding fellow of the Royal Society of Edinburgh. She received the 2009 ACM/AAAI Allen Newell Award, the 2015 IJCAI Award for Research Excellence, and the 2017 Association for Computational Linguistics Lifetime Achievement Award. She was founding dean of science and then dean of Harvard’s Radcliffe Institute for Advanced Study, and she is known for her role in the establishment and leadership of interdisciplinary institutions and for her contributions to the advancement of women in science. Professor Grosz serves on the boards of several scientific, scholarly and academic institutions.


Henry YuenAssistant Professor Computer ScienceUniversity of Toronto

Henry Yuen

Assistant Professor
Computer Science

University of Toronto

A tale of Turing machines, quantum entangled particles, and operator algebras

April 16, 2020

Abstract:
In a recent result known as “MIP* = RE”, ideas from three disparate fields of study — computational complexity theory, quantum information, and operator algebras — have come together to simultaneously resolve long-standing open problems in each field, including a 44-year old mystery in mathematics known as Connes’ Embedding Problem. In this talk, I will describe the evolution and convergence of ideas behind MIP* = RE: it starts with three landmark discoveries from the 1930s (Turing’s notion of a universal computing machine, the phenomenon of quantum entanglement, and von Neumann’s theory of operators), and ends with some of the most cutting-edge developments from theoretical computer science and quantum computing.

This talk is aimed at a general scientific audience, and will not assume any specialized background in complexity theory, quantum physics, or operator algebras.

Bio:
Henry Yuen is an assistant professor in the Computer Science and Mathematics departments at the University of Toronto. His research focuses on the interplay between quantum information, complexity theory, and cryptography. He received his PhD in Computer Science from MIT in 2016, and spent two years as a postdoctoral associate at UC Berkeley before joining the University of Toronto in 2018. He recently received a Google Quantum Research Award.