The institute is proud to join RTI in sponsoring this first annual event focused on bias, fairness, and transparency in machine learning. Help us welcome practitioners and researchers from across the globe to learn more about developments in this field. Register here.

Keynote Speakers

Cynthia Rudin, PhD

Dr. Rudin is a professor at Duke University and directs the Prediction Analysis Lab, whose main focus is interpretable machine learning. In 2019, she was elected as a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics “for her contributions to interpretable machine learning algorithms, prediction in large scale medical databases, and theoretical properties of ranking algorithms.” She is a three-time winner of the INFORMS Innovative Applications in Analytics Award, was named as one of the “Top 40 Under 40” by Poets and Quants in 2015, and was named by as one of the 12 most impressive professors at MIT in 2015.

Jeannette M. Wing, PhD

Dr. Wing is Avanessians Director of the Data Science Institute and Professor of Computer Science at Columbia University. From 2013 to 2017, she was a Corporate Vice President of Microsoft Research. She is currently a member of the American Academy for Arts and Sciences Council; the New York State Commission on Artificial Intelligence, Robotics, and Automation; and the Advisory Board for the Association for Women in Mathematics. She is a Fellow of the American Academy of Arts and Sciences, American Association for the Advancement of Science, the Association for Computing Machinery (ACM), and the Institute of Electrical and Electronic Engineers (IEEE).

Kristian Lum, PhD

Dr. Lum is an assistant research professor at the University of Pennsylvania. She studies and develops machine learning models to tackle problems with social impact. Her work includes statistical population estimation models to estimate the number of undocumented victims of human rights violations, “fair” algorithms for use in high-stakes decision making, and epidemiological models to study disease spread among and between marginalized populations and the broader community. Previously she served as the lead statistician at the Human Rights Data Analysis Group where she led the HRDAG project on criminal justice in the United States.

Francesca Tripodi, PhD

Dr. Tripodi is a sociologist and media scholar at the University of North Carolina at Chapel Hill whose research focuses on subjects like search, political partisanship, media manipulation and inequality. In 2019, she was invited to testify before the Senate Judiciary Committee on her research, explaining how search processes are gamed to maximize exposure and drive ideologically based queries. Her research has been covered by The Washington Post, The New York Times, The New Yorker, The Columbia Journalism Review, Wired, The Guardian and The Neiman Journalism Lab.

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