Tselil Schramm

Tselil Schramm is an assistant professor of Statistics at Stanford University. She is broadly interested in the theory of algorithms, optimization, and computational complexity, especially for problems arising in statistics. Her work aims to develop algorithmic tools for high-dimensional estimation problems and to characterize and explain information-computation tradeoffs. Before joining Stanford she received her PhD from UC Berkeley, and later spent time as a postdoc at Harvard and MIT. She is currently supported by an NSF CAREER award and a Stanford Gabilan Fellowship.

Program Visits

Analysis and TCS: New Frontiers, Summer 2023, Visiting Scientist

Computational Complexity of Statistical Inference, Fall 2021, Visiting Scientist and Program Organizer

Probability, Geometry, and Computation in High Dimensions, Fall 2020, Microsoft Research Fellow

Bridging Continuous and Discrete Optimization, Fall 2017, Google Research Fellow

Foundations of Machine Learning, Spring 2017, Visiting Graduate Student

Algorithms and Uncertainty, Fall 2016, Visiting Graduate Student

Counting Complexity and Phase Transitions, Spring 2016, Visiting Graduate Student

Algorithmic Spectral Graph Theory, Fall 2014, Visiting Graduate Student