Shuvomoy Das Gupta
Shuvo Das Gupta
● Postdoc at Columbia IEOR
● Ph.D. from MIT Operations Research Center, 2024
● Incoming Assistant Professor at Rice CMOR (July 2025-)
● Email: sd3871@columbia.edu
About Me
I am a Postdoctoral Research Scientist at the Department of Industrial Engineering and Operations Research, Columbia University, hosted by Professor Christian Kroer and Professor Garud Iyengar. I recently obtained my Ph.D. from the Operations Research Center at MIT in May 2024. My research is primarily in optimization—both theory and application—and often both simultaneously.
Update. I will join the Department of Computational Applied Mathematics & Operations Research at Rice University as an Assistant Professor starting July 2025.
News
Our BnB-PEP paper is a finalist for the 2024 George Nicholson Student Paper Competition!
I have received the 2024 Informs Computing Society Student Paper Award for the BnB-PEP paper! [citation]
Recently our OptISTA algorithm, discovered using BnB-PEP, has been successfully applied to solve large-scale magnetization transfer imaging problems by a group at NYU School of Medicine (see the Imaging Neuroscience paper by Assländer et al) and has been incorporated into their open-source software package!
Papers
Shuvomoy Das Gupta, Robert M. Freund, Xu Andy Sun, Adrien B. Taylor, “Nonlinear Conjugate Gradient Methods: Worst-case Convergence Rates via Computer-assisted Analyses”, published in Mathematical Programming Series A, 2024. [pdf] [code] [video] [bib]
Shuvomoy Das Gupta, Bartolomeo Stellato, and Bart P.G. Van Parys, “Exterior-point Optimization for Sparse and Low-rank Optimization”, published in the Journal of Optimization Theory and Applications, 2024. [pdf] [NExOS.jl Julia package] [bib]
Shuvomoy Das Gupta, Bart P.G. Van Parys, and Ernest K. Ryu, “Branch-and-Bound Performance Estimation Programming: A Unified Methodology for Constructing Optimal Optimization Methods”, published in Mathematical Programming Series A, 2024. [pdf] [code] [tutorial video] [slides] [bib]
Shuvomoy Das Gupta, Bart P.G. Van Parys, and J. Kevin Tobin, “Energy-optimal Timetable Design for Sustainable Metro Railway Networks”, R&R in Transportation Research Part B: Methodological, 2023. [pdf] [slides] [poster] [bib]
Uijeong Jang, Shuvomoy Das Gupta, and Ernest K. Ryu, “Computer-Assisted Design of Accelerated Composite Optimization Methods: OptISTA”, major revision in Mathematical Programming Series A, 2023. [pdf] [bib]
Shuvomoy Das Gupta and Lacra Pavel, “On Seeking Efficient Pareto Optimal Points in Multi-Player Minimum Cost Flow Problems with Application to Transportation Systems”, published in the Journal of Global Optimization 74 (2019): 523-548. [pdf] [presentation] [bib]
Shuvomoy Das Gupta, “On Convergence of Heuristics Based on Douglas-Rachford Splitting and ADMM to Minimize Convex Functions over Nonconvex Sets”, published in the proceedings of the 56th Allerton Conference on Communication, Control, and Computing, University of Illinois at Urbana-Champaign, IL, USA, October 2018. [pdf] [presentation] [bib]
Shuvomoy Das Gupta and Lacra Pavel, “Multi-player Minimum Cost Flow Problems with Nonconvex Costs and Integer Flows”, published in the proceedings of the 55th IEEE Conference on Decision and Control, Las Vegas, NV, USA, December 12-14, 2016. [pdf] [longer version with proofs] [presentation] [bib]
Shuvomoy Das Gupta, J. Kevin Tobin, and Lacra Pavel, “A Two-Step Linear Programming Model for Energy-Efficient Timetables in Metro Railway Networks”, published in Transportation Research Part B: Methodological 93 (2016): 57–74. [pdf] [bib]
Shuvomoy Das Gupta, Lacra Pavel, and J. Kevin Tobin, “An Optimization Model to Utilize Regenerative Braking Energy in a Railway Network”, published in the proceedings of 2015 American Control Conference (ACC), Chicago, IL, USA, July 2015. [pdf] [presentation] [bib]
Awards
Honorable Mention, MIT Operations Research Center Best Student Paper Award, 2024
Winner, Informs Computing Society Student Paper Award, 2024 [citation]
Finalist, George Nicholson Student Paper Competition, 2024
Media Coverage
Risky Giant Steps Can Solve Optimization Problems Faster by Allison Parshall, Quanta Magazine, August 2023. [Quanta Article]
Also publicized in the Chinese magazine 机器之心 (Heart of the Machine), which is a well-known outlet in China for staying updated on advancements in AI, machine learning, data science, and related fields.
Also publicized in the Nautilus Magazine on September 5, 2023.
Talks
Energy-optimal Timetable Design for Sustainable Metro Railway Networks [slides]
2023 INFORMS Annual Meeting in Phoenix, AZ, October 16, 2023
33rd Annual POMS Conference, Orlando, FL, May 21 - 25, 2023
(Poster) 2023 MIT Energy Initiative Annual Research Conference
BnB-PEP: A Unified Methodology for Constructing Optimal Optimization Methods [video] [slides] [poster]
2023 INFORMS Annual Meeting in Phoenix, AZ, October 17, 2023
SIAM Conference on Optimization (OP23), May 31 - June 3, 2023, Seattle, Washington, U.S.
(Poster) Cornell Young Researcher's Workshop, October 6-8, 2022
Nonlinear Conjugate Gradient Methods: Worst-case Convergence Rates via Computer-assisted Analyses
ORC Student Seminar, February, 2022
Design and Analysis of First-order Methods via Nonconvex QCQP Frameworks [video]
Workshop on Performance Estimation Problems, UCLouvain, Belgium, February 13-14, 2023.
NExOS.jlfor Nonconvex Exterior-point Optimization [Youtube video]Exterior-point Optimization for Sparse and Low-rank Optimization [Slides]
Seoul National University, November 17, 2020 (talk given to Professor Ernest Ryu's research group)
INFORMS Annual Meeting, November 10, 2020
MIT LIDS student conference, January 2021
On seeking efficient Pareto optimal points in multi-player minimum cost flow problems [Slides]
MIT LIDS student conference, January 2020
On Convergence of Heuristics Based on Douglas-Rachford Splitting and ADMM to Minimize Convex Functions over Nonconvex Sets
56th Allerton Conference on Communication, Control, and Computing, October, 2018
Teaching
6.7220: Nonlinear Optimization (Spring, 2023) [Teaching score: 6.9/7]
Teaching assistant for a course that aims to provide PhD students with a unified overview of convex optimization.
Duties: Assisting students, leading recitations, writing and marking assignments and exams.
Pdf of my recitation lectures: [pdf]
15.S60: Computing in Optimization and Statistics (2023) [Teaching score: 7/7]
Instructor for the advanced optimization session. [Jupyter notebook 1] [Jupyter notebook 2] [Student feedback]
15.S60: Computing in Optimization and Statistics (2022) [Teaching score 6.8/7]
Instructor for the advanced optimization session. [Jupyter notebook 1] [Jupyter notebook 2] [Student feedback]
15.S08: Optimization of Energy Systems (Spring 2022) [Teaching score 6.0/7]
Teaching assistant for a course that aims to lead PhD or advanced master students to the forefront of energy system research.
Duties: Developing implementations of next generation power system models, assisting students, leading recitations, writing and marking assignments and exams.
Software
NExOS.jl[github repo]BnB-PEP code[github repo]NCG-PEP code[github repo]
Service
Reviewer for:
Mathematical Programming
Transportation Research Part B: Methodological
IEEE Transactions on Control of Network Systems
American Control Conference
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Automatic Control
Session Chair, INFORMS Annual Meeting, 2022
Session Chair, INFORMS Annual Meeting, 2023
PhD Thesis
Advances in Computer-Assisted Design and Analysis of First-Order Optimization Methods and Related Problems [pdf]
MASc Thesis
Optimization Models for Energy-efficient Railway Timetables. [pdf]