Chara Podimata

Chara Podimata is the Class of 1942 Career Development Assistant Professor and Assistant Professor of Operations Research/Statistics at MIT Sloan School of Management. She joined MIT in 2023 after completing her PhD at Harvard University and a postdoctoral fellowship at UC Berkeley through the FODSI program. She is affiliated with the Operations Research Center (ORC) at MIT and serves as a Lead Researcher at Archimedes/Athena RC.

Her research focuses on the intersection of Theoretical Computer Science, Economics, and Machine Learning, with particular emphasis on incentive-aware machine learning, social computing, online learning, and mechanism design. She investigates how humans adapt to machine learning algorithms used for consequential decision-making, exploring policy questions related to AI and recommendation systems.

Dr. Podimata's recent work shows strong trends in strategic classification, recommendation systems with strategic users, and fairness in algorithmic decision-making. Her publications span top venues including NeurIPS, EC, WINE, and AISTATS, with increasing focus on real-world applications of incentive-aware learning systems.

• Amazon Research Award (2023)
• MacArthur Foundation x-grant
• Google Research Scholar Award (2025)
• MIT grant from the GenAI Consortium (MGAIC)
• Microsoft Dissertation Grant
• Siebel Scholarship

She actively advises multiple PhD students at MIT ORC and EECS, as well as MBAn students. Her research has been supported by industry partnerships with Amazon, Google, and Microsoft. She maintains strong connections with industry through internships she completed during her PhD at Microsoft Research and Google.

Dr. Podimata leads a research group focused on understanding human-algorithm interactions, with particular attention to how users strategically adapt to recommendation and decision systems. Her team works at the cutting edge of developing theoretically sound yet practically applicable approaches to incentive-aware machine learning.