Tselil Schramm is freshly graduated from a PhD in Computer Science at UC Berkeley. During her PhD, she was advised by Prasad Raghavendra and Satish Rao, and was supported by a National Science Foundation Fellowship and a UC Berkeley Chancellor's Fellowship. Her research interests include spectral algorithms, spectral graph theory, convex programming, and approximation algorithms.
- 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.