A Discussion on Fairness in Machine Learning with Georgia Tech Faculty

Fairness in machine learning and artificial intelligence is a hot, and important topic in tech today. Join Georgia Tech faculty members Judy Hoffman, Rachel Cummings, Deven Desai, and Swati Gupta for a panel discussion on their work in regards to fairness and their motivations behind it. Sponsored by the Machine Learning Center at Georgia Tech.

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About the Panelists

 

Judy Hoffman

Judy Hoffman is an assistant professor in the School of Interactive Computing. She recently joined Georgia Tech from Facebook AI Research. Hoffman brings a wealth of knowledge at the intersection of computer vision and machine learning. Her research tackles real-world variation and scale while minimizing human supervision. Hoffman develops learning algorithms that facilitate the transfer of information through semi-supervised and unsupervised model generalization and adaptation. Her thesis focused on transferrable representation learning for visual recognition.

Hoffman was previously a postdoctoral researcher at UC Berkeley after earning a Ph.D. in electrical engineering and computer engineering from UC Berkeley as well. She is a recipient of the NSF Graduate Fellowship and the Rosalie M. Stern Fellowship.

Rachel Cummings

Dr. Rachel Cummings is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Her research interests lie primarily in data privacy, with connections to machine learning, algorithmic economics, optimization, statistics, and information theory. Her work has focused on problems such as strategic aspects of data generation, incentivizing truthful reporting of data, privacy-preserving algorithm design, impacts of privacy policy, and human decision-making.

Dr. Cummings received her Ph.D. in Computing and Mathematical Sciences from the California Institute of Technology, her M.S. in Computer Science from Northwestern University, and her B.A. in Mathematics and Economics from the University of Southern California.

She is the recipient of a Google Research Fellowship, a Simons-Berkeley Research Fellowship in Data Privacy, the ACM SIGecom Doctoral Dissertation Honorable Mention, the Amori Doctoral Prize in Computing and Mathematical Sciences, a Caltech Leadership Award, a Simons Award for Graduate Students in Theoretical Computer Science, and the Best Paper Award at the 2014 International Symposium on Distributed Computing.   Dr. Cummings also serves on the ACM U.S. Public Policy Council's Privacy Committee.

Swati Gupta

Dr. Swati Gupta is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Prior to her arrival at Georgia Tech, she spent two semesters as a Fellow at the Simons Institute, UC Berkeley, participating in programs on Bridging Continuous and Discrete Optimization and Real-time Decision Making. She received her Ph.D. in operations research from the Massachusetts Institute of Technology Operations Research Center and a dual degree (B.Tech and M.Tech) in computer science and engineering from the Indian Institute of Technology, Delhi.

Gupta's research interests lie primarily in combinatorial, convex, and robust optimization with applications in online learning and data-driven decision-making under partial information. Her work focuses on speeding up fundamental bottlenecks that arise in learning problems due to the combinatorial nature of the decisions, as well as drawing from machine learning to improve traditional optimization methods.

She has worked on providing optimized inventory routing decisions under uncertain demand, and pricing items optimally while incorporating effects of sales and promotions. She has collaborated with industrial research labs such as the IBM Research Lab in Zurich, Switzerland and the Oracle Retail Data Science Group. Gupta is further interested in exploring strategic behavior of customers, fairness and bias in decisions, and unintended consequences of optimization.

Gupta was the Microsoft Research Fellow at Simons Institute in Spring 2018, and she received the prestigious Simons-Berkeley Research Fellowship for the academic year 2017-18. Her collaborative work on systematically evaluating heuristics and understanding which heuristic or algorithm works best on unseen problem instances received a special recognition from the INFORMS Computing Society in their Student Paper Competition in 2016. She was also a finalist for the INFORMS Service Science Student Paper Competition for her work on promotion optimization for retail items. Gupta received the Google Women in Engineering Award in India in 2011.

Deven Desai (moderator)

Deven Desai joined the Scheller faculty in fall of 2014 in the Law and Ethics Program. Prior to joining Scheller, Professor Desai was an associate professor of law at the Thomas Jefferson School of Law. He was also the first, and to date, only Academic Research Counsel at Google, Inc., and a Visiting Fellow at Princeton University's Center for Information Technology Policy.

Professor Desai's scholarship examines how business interests, new technology, and economic theories shape privacy and intellectual property law and where those arguments explain productivity or where they fail to capture society's interest in the free flow of information and development. His work has appeared in leading law reviews and journals including the Georgetown Law Journal, Minnesota Law Review, Notre Dame Law Review, Wisconsin Law Review, U.C. Davis Law Review, Florida Law Review, and Brigham Young University Law Review.

Prior to becoming a professor, Desai has been a litigator handing intellectual property and technology matters with Quinn, Emanuel, Urquhart, & Sullivan, LLP, in-house counsel for an idealab! Internet infrastructure company, and part of policy and fundraising teams on the 2002 Cory Booker for Mayor campaign.

Professor Desai has been interviewed about 3D printing, intellectual property, privacy, and technology by the New York Times and the news show, Take Part Live. He blogs about technology, intellectual property, and privacy at Concurring Opinions and Madisonian.

He is a graduate of the University of California, Berkeley with highest honors and the Yale Law School, where he was co-editor-in-chief of the Yale Journal of Law & the Humanities.

Event Details

Date/Time:

  • Wednesday, November 6, 2019
    12:15 pm - 1:15 pm
Location: Marcus Nanotechnology Building, Rooms 1116-1118

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