Swati Gupta


Swati Gupta

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Swati Gupta is an Assistant Professor at the MIT Sloan School of Management in the Operations Research and Statistics Group.

Previously, she was a Fouts Family Early Career Professor and Assistant Professor at the Stewart School of Industrial & Systems Engineering at Georgia Tech. She also served as the lead of Ethical AI in the NSF AI Institute on Advances in Optimization, awarded in 2021.

Her research interests include optimization and machine learning, with a focus on algorithmic fairness. Her work spans various domains such as hiring, admissions, e-commerce, quantum optimization, and energy.

She received the NSF CAREER Award in 2023, the Class of 1934: Student Recognition of Excellence in Teaching in 2020 and 2021 at Georgia Tech, the JP Morgan Early Career Faculty Recognition in 2021, the NSF CISE Research Initiation Initiative Award in 2019, and the Google Women in Engineering Award (India) in 2011. She was also awarded the prestigious Simons-Berkeley Research Fellowship in 2017-2018, where she was selected as the Microsoft Research Fellow in 2018. Her research and students have received recognition at various venues like INFORMS Doing Good with OR 2022 (finalist), INFORMS Undergraduate Operations Research 2018 (honorable mention), INFORMS Computing Society 2016 (special recognition), and INFORMS Service Science Student Paper 2016 (finalist). Dr. Gupta’s research is partially funded by the National Science Foundation and DARPA.

Swati received a PhD in operations research from MIT in 2017, and joint Master’s and Bachelor in Technology in computer science from IIT Delhi in 2011.


Gupta receives CAREER award

July 5, 2023

Gutpa wins early career award

June 4, 2021

Gupta wins student recognition for excellence in teaching at Georgia Tech

June 20, 2020

Gupta honored with CRII award

June 1, 2019

Gupta wins research fellowship

May 15, 2018

Gupta receives Google India Women in Engineering Award

August 28, 2011


"Too many Fairness Metrics: Is there a solution? Equity across Demographic Groups for the Facility Location Problem."

Gupta, Swati, Akhil Jalan, Gireeja Ranade, Helen Yang, and Simon Zhuang (Accepted with minor revision). Fields Institute Communication Series. Forthcoming.

"Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths."

Tate, Reuben, Jai Moondra, Bryan Gard, Greg Mohler, and Swati Gupta. Quantum Vol. 7, (2023): 1121.

"Which Lp Norm is the Fairest? Approximations for Fair Facility Location Across all 'p'."

Jai Moondra, Swati Gupta, and Mohit Singh (Journal version, under submission). In EC '23: Proceedings of the 24th ACM Conference on Economics and Computation, July 2023. arXiv.

"Using Algorithms to Tame Discrimination: A Path To Algorithmic Diversity, Equity and Inclusion."

Desai, Deven R., Swati Gupta, Jad Salem. UC Davis Law Review, April 2023.

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