Coca-Cola Foundation Professor
Education
- Ph.D. Algorithms, Combinatorics and Optimization (2008), Tepper School of Business, Carnegie Mellon Univeristy
- M.S. Algorithms, Combinatorics and Optimization (2005), Tepper School of Business, Carnegie Mellon Univeristy
- B. Tech. Computer Science and Engineering (1999), Indian Institute of Technology, Delhi
About
Mohit Singh is a Coca-Cola Foundation Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the Director of the Algorithms and Randomness Center (ARC). Prior to this, he served as a researcher in the Theory Group at Microsoft Research in Redmond, Washington.
Previously, Singh was an assistant professor at McGill University from 2010-2011 and a postdoctoral researcher at Microsoft Research, New England from 2008-2009.
He obtained his Ph.D. in 2008 from the Tepper School of Business at Carnegie Mellon University.
Research
Singh’s research interests include discrete optimization, approximation algorithms, and convex optimization. His research is focused on optimization problems arising in cloud computing, logistics, network design, and machine learning.
Singh’s research interests include discrete optimization, approximation algorithms, and convex optimization. His research is focused on optimization problems arising in cloud computing, logistics, network design, and machine learning.
Singh received the Tucker Prize in 2009 given by the Mathematical Optimization Society for an outstanding doctoral thesis on “Iterative Methods in Combinatorial Optimization.” He also received the best paper award for his work on the traveling salesman problem at the Annual Symposium on Foundations of Computer Science (FOCS) in 2011.
Representative Publications
- Lau, L. C., Ravi, R., & Singh, M. (2011). Iterative Methods in Combinatorial Optimization. Cambridge University Press.
- An, H.-C., Singh, M., & Svensson, O. (2017). LP-based Algorithms for Capacitated Facility Location. SIAM Journal on Computing.
- Singh, M., & Lau, L. C. (2015). Approximating Minimum Bounded Degree Spanning Trees to Within One of Optimal. Journal of the ACM.
- Lau, L. C., Naor, J., Salavatipour, M. R., & Singh, M. (2009). Survivable Network Design with Degree or Order Constraints. SIAM Journal on Computing.
- Samadi, S., Tantipongpipat, U., Morgenstern, J., Singh, M., & Vempala, S. (2018). The Price of Fair PCA: One Extra Dimension. Advances in Neural Information Processing Systems (NeurIPS).
- Oveis Gharan, S., Saberi, A., & Singh, M. (2011). A Randomized Rounding Approach to the Traveling Salesman Problem. IEEE Symposium on Foundations of Computer Science (FOCS).
- Brown, A., Laddha, A., Pittu, M., Singh, M., & Tetali, P. (2022). Determinant Maximization via Matroid Intersection Algorithms. IEEE Symposium on Foundations of Computer Science (FOCS).
- Perez-Salazar, S., Singh, M., & Toriello, A. (2025). The IID Prophet Inequality with Limited Flexibility. Mathematics of Operations Research.
- Brown, A., Laddha, A., Pittu, M., & Singh, M. (2025). Approximation Algorithms for the Weighted Nash Social Welfare via Convex and Non-Convex Programs. Mathematical Programming.