Yuval Emek graduated summa cum laude from Technion – Israel Institute of Technology with a bachelor degree in computer science (2000) and completed his master studies (2003) and Ph.D. (2008) in computer science and applied mathematics at Weizmann Institute of Science under the advise of David Peleg. Following that, he held post-doc positions at Tel Aviv University (2008-2009, Boaz Patt-Shamir’s group), Microsoft (2009-2010, Moshe Tennenholtz’s group), and ETH Zurich (2010-2013, Roger Wattenhofer’s group). In 2013, Yuval joined the Faculty of Industrial Engineering and Management in the Technion.
Go to my home page for an updated publication list (with links to the actual papers)
- Stone Age Distributed Computing. Yuval Emek and Roger Wattenhofer. In Proceedings of the 32nd ACM Symposium on Principles of Distributed Computing (PODC), pages 137–146, 2013.
- Approximating the Statistics of various Properties in Randomly Weighted Graphs. Yuval Emek, Amos Korman, and Yuval Shavitt. In Proceedings of the 22nd ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 1455–1467, 2011.
- Adversarial Leakage in Games. Noga Alon, Yuval Emek, Michal Feldman, and Moshe Tennenholtz. SIAM Journal on Discrete Mathematics (SIDMA) 27(1), pp. 363–385, 2013. A preliminary version appeared in I(T)CS 2010.
- SINR Diagrams: Towards Algorithmically Usable SINR Models of Wireless Networks. Chen Avin, Yuval Emek, Erez Kantor, Zvi Lotker, David Peleg, and Liam Roditty. Journal of the ACM (JACM), 59(4), pp. 18:1–18:34, 2012. A preliminary version appeared in PODC 2009.
- New Bounds for the Controller Problem. Yuval Emek and Amos Korman. Distributed Computing (DC) 24(3), pp. 177–186, 2011. A preliminary version appeared in DISC 2009.
- Lower-Stretch Spanning Trees. Michael Elkin, Yuval Emek, Daniel A. Spielman, and Shang-Hua Teng. SIAM Journal on Computing (SICOMP) 38(2), pp. 608–628, 2008. A preliminary version appeared in STOC 2005.
- Approximating Minimum Max-Stretch Spanning Trees on Unweighted Graphs. Yuval Emek and David Peleg. SIAM Journal on Computing (SICOMP) 38(5), pp. 1761–1781, 2008. A preliminary version appeared in SODA 2004.
Discrete algorithms for decision makers that cannot see the whole picture, e.g., because it is too big (the streaming model), too far (distributed computing), too early (online algorithms), or too private (algorithmic game theory)
Network algorithms, discrete optimization,