Algorithm design; algorithmic game theory
Current Research Interest
Quantifying efficiency in games; learning in games; learning with partial information feedback; approximation algorithms
Institute of Electrical and Electronic Engineers John Von Neumann Medal
National Academy of Engineering
National Academy of Sciences
American Academy of Arts and Sciences
European Association for Theoretical Computer Science Gödel Prize
Cook Award as adviser of Women in Computing at Cornell (WICC)
Roughgarden, Tim, and Éva Tardos. “How Bad is Selfish Routing?” Journal of the ACM 49, no. 2 (2002): 236-259.
Lykouris, Thodoris, Vasilis Syrgkanis, and Éva Tardos. “Learning and Efficiency in Games with Dynamic Population.” In SODA ’16 Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, edited by Robert Kraughgamer, 120-129. Philadelphia: Society for Industrial and Applied Mathematics, 2016.