Swati Gupta

Swati Gupta is the Class of 1947 Career Development Associate Professor and an Associate Professor at the MIT Sloan School of Management in the Operations Research and Statistics Group. Her work focuses on deep theoretical questions in optimization and AI, aiming to bridge the gap between rigorous theory and meaningful practice. She broadly works on static and dynamic algorithms for incomplete and erroneous data, multi-criteria decision-making using optimization and learning, and bridging discrete, continuous, and quantum optimization. Her research spans domains such as hiring, admissions, districting, e-commerce, platforms, supply chains, healthcare, quantum optimization, and energy. She frequently collaborates with industry and scholars across disciplines, including doctors, physicists, and law and policy experts.

Swati Gupta is an Associate Professor at the Sloan School of Management, MIT, specializing in Optimization, Ethical AI and ML, Societal Systems, and Quantum Computing. Her research explores the intersection of algorithmic fairness, optimization techniques, and their societal implications. She investigates quantum optimization methods, such as quantum annealing and variational quantum algorithms, to solve complex combinatorial problems. Gupta also focuses on fairness in machine learning, particularly individual and group fairness, and their application in real-world systems like public school admissions and facility location. Her work emphasizes algorithmic transparency, equity, and the computational challenges of ensuring fairness in decision-making processes.