Thomas Courtade

Thomas Courtade is an Associate Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He joined Berkeley in 2014 after a postdoctoral fellowship at Stanford University, supported by the NSF Center for Science of Information. His research focuses on information theory, data science, and their intersections with machine learning and privacy-preserving algorithms.

Education:

• Ph.D. in Electrical Engineering, University of California, Los Angeles (2012)
• M.Sc. in Electrical Engineering, University of California, Los Angeles (2008)
• B.Sc. in Electrical Engineering, Michigan Technological University (2007, summa cum laude)

Research Interests:

• Information Theory and its applications to network communication
• Privacy-preserving data analysis and differential privacy
• Statistical estimation under heterogeneous privacy constraints
• Optimization in distributed systems and market design
• Functional inequalities (Brascamp-Lieb, Poincaré-Korn)
• Machine learning with emphasis on model robustness and efficiency

Awards and Fellowships:

• Electrical Engineering Award for Outstanding Teaching (2020)
• Hellman Fellow (2016)

Advising and Grants:

• Supervised no listed students (student names not provided in text)
• Recipient of NSF CAREER Award (2018)

Labs and Collaborations:

• Berkeley Laboratory for Information and System Sciences (BLISS)
• Center for Theoretical Foundations of Learning, Inference, and Mathematics (CLIMB)