Anupam Gupta received his Ph.D. in computer science from UC Berkeley in 2000, advised by Alistair Sinclair. He was a postdoc at Cornell University and Lucent Bell Labs before joining Carnegie Mellon University. His research interests are in algorithms, particularly in approximation algorithms (most recently related to problems in stochastic optimization), online algorithms, and the algorithmic implications of metric space embeddings.
- Theory of Reinforcement Learning, Fall 2020. Visiting Scientist.
- Foundations of Data Science, Fall 2018. Visiting Scientist.
- Bridging Continuous and Discrete Optimization, Fall 2017. Visiting Scientist.
- Algorithms and Uncertainty, Fall 2016. Visiting Scientist, Program Organizer and Workshop Organizer.