Swati Gupta

Fouts Family Early Career Professor
Assistant Professor


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  • Swati Gupta Google Scholar


  • Ph.D. Operations Research (2017), Massachusetts Institute of Technology
  • B.Tech & M.Tech Computer Science and Engineering (2011), Indian Institute of Technology, Delhi


  • Combinatorial, Convex and Robust Optimization
  • Online and Machine Learning
  • Fairness and Bias in Decisions


Dr. Swati Gupta is a Fouts Family Early Career Professor and Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Prior to her arrival at Georgia Tech, she spent two semesters as a Fellow at the Simons Institute, UC Berkeley, participating in programs on Bridging Continuous and Discrete Optimization and Real-time Decision Making. She received her Ph.D. in operations research from the Massachusetts Institute of Technology Operations Research Center and a dual degree (B.Tech and M.Tech) in computer science and engineering from the Indian Institute of Technology, Delhi.

Gupta's research interests lie primarily in combinatorial, convex, and robust optimization with applications in online learning and data-driven decision-making under partial information. Her work focuses on speeding up fundamental bottlenecks that arise in learning problems due to the combinatorial nature of the decisions, as well as drawing from machine learning to improve traditional optimization methods.

She has worked on providing optimized inventory routing decisions under uncertain demand, and pricing items optimally while incorporating effects of sales and promotions. She has collaborated with industrial research labs such as the IBM Research Lab in Zurich, Switzerland and the Oracle Retail Data Science Group. Gupta is further interested in exploring strategic behavior of customers, fairness and bias in decisions, and unintended consequences of optimization.

Gupta was the Microsoft Research Fellow at Simons Institute in Spring 2018, and she received the prestigious Simons-Berkeley Research Fellowship for the academic year 2017-18. Her collaborative work on systematically evaluating heuristics and understanding which heuristic or algorithm works best on unseen problem instances received a special recognition from the INFORMS Computing Society in their Student Paper Competition in 2016. She was also a finalist for the INFORMS Service Science Student Paper Competition for her work on promotion optimization for retail items. Gupta received the Google Women in Engineering Award in India in 2011.

Awards and Honors

  • Simons-Berkeley Research Fellowship for Bridging Continuous and Discrete Optimization and Real-Time Decision Making Programs Fall 2017 - Spring 2018
  • Special Recognition in the INFORMS Computing Society Student Paper Competition for the paper "What Works Best When? A Framework for Systematic Heuristic Evaluation", joint work with John Silberholz and Iain Dunning. Fall 2016
  • Finalist in the INFORMS Service Section Student Paper Competition for the paper "Efficient Algorithm for Dynamic Pricing using a Graphical Representation", joint work with Maxime Cohen, Jeremy Kalas and Georgia Perakis. Fall 2016
  • Google Women in Engineering Award 2011