Friday, April 5, 2019 | MIT Media Lab E14-674


As part of the MIT Institute for Data, Systems, and Society (IDSS), the Statistics and Data Science Center (SDSC) is a MIT-wide focal point for advancing academic programs and research activities in statistics and data science. SDSCon will be a celebration and community-building event for those interested in statistics. Discussions will cover applications of statistics and data science across a wide range of fields and approaches.


Introductory Remarks by Anantha P. Chandrakasan, Dean of the MIT School of Engineering, Vannevar Bush Professor of Electrical Engineering and Computer Science

Plenary Talk 1: “Leveraging Data science, Experiments, and Informal Social Networks for the Common Good: The Example of Immunization” by Esther Duflo, Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics, MIT

Interfaces and Transitions Session

“Luck and the Law: Quantifying Chance in Fantasy Sports and Other Contests” by Peko Hosoi, Associate Dean of Engineering & Neil and Jane Pappalardo Professor of Mechanical Engineering, MIT

“Dynamic Pricing and Matching for Ride-Hailing” by Dawn Woodard, Director of Data Science – Maps, UBER & Adjunct Professor, Cornell University

“Improving Subseasonal Forecasting in the Western U.S. with Machine Learning” by Lester Mackey, Statistical Machine Learning Researcher, Microsoft Research & Adjunct Professor, Stanford University

Plenary Talk 2: “Reinforcement Learning” by John Tsitsiklis, Clarence J Lebel Professor of Electrical Engineering and Computer Science & Director of Laboratory for Information and Decision Systems (LIDS), MIT

Social Sciences Session

“Data-driven Policy Analysis for the 21st Century” by Alberto Abadie, Professor of Economics & Associate Director of IDSS

“The Ethical Algorithm” by Aaron Roth, Class of 1940 Bicentennial Term Associate Professor of Computer and Information Science, University of Pennsylvania

“Markets and Mechanisms for Public Decision Making” by Ashish Goel, Professor of Management Science and Engineering and, (by courtesy) of Computer Science, Stanford University

MIT Session

“Capacity Lower Bound for the Ising perceptron” by Nike Sun, Associate Professor, MIT
From Profiles to Causal Mechanisms: Design for Inference in biology: Aviv Regev, Professor of Biology, MIT & Core Member, Broad Institute


Closing Remarks by Devavrat Shah, Professor of Electrical Engineering and Computer Science & Director of Statistics and Data Science Center, MIT