Suvrajeet Sen
| Suvrajeet Sen | |
|---|---|
| Born | |
| 🎓 Alma mater | Virginia Tech |
| 💼 Occupation | |
Suvrajeet Sen is a professor of Industrial Systems Engineering at University of Southern California, specializing in optimization and modeling for infrastructure systems, with a focus on large scale, stochastic and integer optimization.
Early Life and Education[1]
Suvrajeet Sen grew up in Bombay (Mumbai) India, spending his time fairly evenly between high school math, cricket, and music (“Bollywood”). He obtained a B.E.(Hons.) in Mechanical Engineering from the well-known BITS, Pilani, in 1977. He moved to the U.S. in search of a great education, and ended up at Virginia Tech pursuing a Ph.D. in Operations Research. OR had already become his academic love during his undergraduate years at BITS. Under the guidance of Hanif Sherali, and Allen Soyster, he studied what was then a newly-found orientation (Balas’ disjunctive programming) for integer programming, and with Soyster he picked up the nascent ideas of robust optimization (RO), and stochastic programming (SP).
Career
After finishing his Ph.D., Suvrajeet Sen spent a year as a Visiting Researcher at Penn State, followed by faculty positions at University of Arizona, Ohio State University, and then University of Southern California. Between 2003 and 2005, Sen served as a program director at NSF where he was responsible for the Operations Research, and the Service Enterprise Engineering programs. At NSF, he also headed the Cyber infrastructure planning activities of the Engineering Directorate. Concurrently with his appointment at NSF, he was a professor of Systems and Industrial Engineering at the University of Arizona.
Sen has devoted most of his research to developing algorithms which will respond efficiently to iteratively-enlarging data sets which simulate the process of discovering alternative data-evolution paths. He is grateful to NSF for investing in this paradigm continuously since 1991, and AFOSR since 2007.
Sen has served on the editorial board of several journals, including Operations Research as Area Editor for Optimization, and as Associate Editor in INFORMS Journal on Computing, Telecommunications Systems, as well as Operations Research. He is the past-Chair of the INFORMS Telecommunications Section and founded the INFORMS Optimization Section.
Honors
Sen was elected a Fellow of INFORMS in 2005.[2] He was the co-winner of INFORMS Computing Society Award in 2015 for seminal work on Stochastic Mixed Integer Programming. In 2017, he was a recipient of INFORMS Distinguished Service Award. Sen was one of the Plenary Speakers at the INFORMS Annual Meeting, 2016, Nashville, TN. He is a member of the Scientific Research Honor Society Sigma Xi.
Selected Publications
J.L. Higle and S. Sen, “Stochastic Decomposition: An algorithm for two stage stochastic linear programs with recourse," Math. of Operations Research, 16, pp. 650-669, 1991.
S. Sen, R.D. Doverspike and S. Cosares, “Network Planning with Random Demand," Telecommunication Systems, 3, pp. 11-30, 1994.
S. Sen and K.L. Head “Controlled Optimization of Phases (COP) at an Intersection," Transportation Science, 31, pp. 5-17, 1997.
S. Sen and J.L. Higle, “The C3 Theorem and a D2 Algorithm for Large Scale Stochastic Integer Programming,” Mathematical Programming, 104, pp. 1-20, 2005.
S. Sen, “Algorithms for Stochastic Mixed-Integer Programming Models," Handbook of Discrete Optimization, (K. Aardal, G.L. Nemhauser, and R. Weismantel eds.), North-Holland Publishing Co., pp. 515-558, 2005.
S. Sen and H.D. Sherali, “Decomposition with Branch-and- Cut Approaches for Two Stage Stochastic Integer Programming," Mathematical Programming, 106, pp. 203-223, 2006.
S. Sen and Y. Liu, “Mitigating Uncertainty via Compromise Decisions in Stochastic Linear Programming: Variance Reduction" Operations Research, 64(6):1422-1437, 2016.
J.Liu and S. Sen, “Asymptotic Results on Two-stage Stochastic Quadratic Programming” SIAM J. on Optimization, vol. 30#1, pp. 823-854, 2020.
Sen also wrote a couple of tutorials on Stochastic Integer Programming.
S. Sen, “Algorithms for Stochastic Mixed-Integer Programming Models," Handbook of Discrete Optimization, (K. Aardal, G.L. Nemhauser, and R. Weismantel eds.), North-Holland Publishing Co., pp. 515-558, 2005.
S. Küçükyavuz and S. Sen, "Introduction to Two-stage Stochastic Mixed Integer Programming" in INFORMS TutORials, pp. 1-27, 2017.
References
- ↑ "People - USC Data Driven Decisions Lab". sites.google.com. Retrieved 2020-12-21.
- ↑ INFORMS. "Fellows: Alphabetical List". INFORMS. Retrieved 2020-12-10.
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