Jérôme Thai

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I am a Ph.D. student in Electrical Engineering and Computer Sciences at UC Berkeley with a minor in Statistics. My advisor is Professor Alex Bayen.

I am interested in statistical learning and convex optimization methods, with applications to selfish routing games and mobility-on-demand systems.

I work with the Foundations Of Resilient CybEr-physical Systems (FORCES) project, which is founded by the U.S. National Science Foundation (NSF). I am also part of the Berkeley Artificial Intelligence Research (BAIR) Lab and work with the Lawrence Berkeley National Laboratory (LBNL). I have worked with the California Center for Innovative Transportation (CCIT), and the Partners for Advanced Transportation Technology (PATH).

My training is in statistical learning, theoretical statistics, operations research, control theory, and convex optimization.

email: jerome.thai at berkeley dot edu.

Industry experience

  • Google research: Software engineer intern, conducting research on the training of neural networks using self-learning algorithms.

  • Lyft: Data Scientist intern in the Pricing division. My work on designing and developping an online ML algorithm for pricing led to the largest improvement in Lyft's core pricing algorithm over the past two years

  • Oracle: Software engineer intern within the Product Quality Analytics team


  • Ph.D., UC Berkeley, EECS, expected end of 2017

  • M.S., UC Berkeley, EECS, expected Spring 2017

  • M.S., Columbia University, Operations Research

  • M.S., École Polytechnique, Applied Mathematics

  • B.S., École Polytechnique, Applied Mathematics

  • Undergraduate in Theoretical Math, Lycée Sainte-Geneviève, Versailles

  • Undergraduate in Theoretical Math, Lycée Louis-le-Grand, Paris