Shuvomoy Das Gupta


Shuvomoy Das Gupta
Ph.D. Student
Operations Research Center

About Me

Hello world! I am a fourth year Ph.D. student at the Operations Research Center at MIT co-advised by Professor Robert M. Freund and Professor Bart Van Parys.

My research focuses on developing efficient algorithms for large-scale optimization and machine learning. I have recently worked on BnB-PEP, which is the first unified methodology to construct optimal first-order algorithms for convex and nonconvex optimization.

I obtained my M.A.Sc. (GPA 4.00/4.00) from the ECE Department, University of Toronto in 2016. After that, I worked as a researcher at the Research & Technology Department of Thales Canada for almost three years. My M.A.Sc. research work on optimization models to compute energy-efficient railway timetables has been integrated with the largest installed base of communication based train control systems worldwide. Previously, I obtained my B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology.



  • BnB-PEP: A Unified Methodology for Constructing Optimal Optimization Methods [video] [slides] [poster]

  • NExOS.jl for Nonconvex Exterior-point Optimization [Youtube video]

  • Exterior-point Optimization for Nonconvex Learning [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 [Slides]

    • Allerton Conference on Communication, Control, and Computing, October 2018

  • Multi-player minimum cost flow problems with nonconvex costs and integer flows [Slides]

    • IEEE Conference on Decision and Control, December 2016

  • An Optimization Model to Utilize Regenerative Braking Energy in a Railway Network [Slides]

    • American Control Conference, July 2015


  • 15.066: System Optimization (Summer 2022)

  • 15.S08: Optimization of Energy Systems (Spring 2022)

    • Teaching assistant for a course that aims to aims to lead PhD or advanced master students to the forefront of energy system research.

    • Duties: Developing Julia implementations of next generation power system models, assisting students, leading recitations, writing and marking assignments and exams.

  • 15.S60: Computing in Optimization and Statistics (2022)

  • 15.093: Optimization Methods (Fall 2020)

    • Teaching assistant for a course that aims to provide masters students with a unified overview of the main algorithms and areas of application in optimization.

    • Duties: Assisting students, leading recitations, writing and marking assignments and exams.

Cumulative GPA


Courses taken

  • [6.251] Introduction to Mathematical Programming

  • [6.436] Fundamentals of Probability

  • [6.252] Nonlinear Optimization

  • [6.881] Optimization for Machine Learning

  • [9.521] Mathematical Statistics

  • [6.860] Statistical Learning Theory

  • [18.456] Algebraic Techniques and Semidefinite Optimization


MASc Thesis

Optimization Models for Energy-efficient Railway Timetables. (Grade: A+) [pdf] [html presentation]