Research

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I study the theoretical foundations and limits of machine learning algorithms. My current research focuses on Sample Complexity, Interpretable Machine Learning, Security, and (non-parametric) Empirical Bayes.

I also enjoy working on problems in classical Information Theory, particularly those related to guessing, data compression, and information measures.

Short Bio

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2022 - present	Associate Professor of Information Theory Information Processing and Communications Laboratory, Télécom Paris (IP Paris)
2017 - 2021	Ph.D. in Information Theory Signal and Information Processing Laboratory, ETH Zurich Thesis: Guess What? Adviser: Prof. Amos Lapidoth
2017	M.Sc. in Electrical Engineering ETH Zurich

My complete CV is available here.