Chara Podimata

Chara Podimata is the Class of 1942 Career Development Assistant Professor of Operations Research and Statistics at MIT Sloan School of Management. She holds a joint appointment as a Lead Researcher at Archimedes/Athena Research Center. Her work focuses on incentive-aware machine learning, strategic interactions in algorithms, and the societal impacts of AI systems. Prior to MIT, she was a FODSI Postdoctoral Fellow at UC Berkeley and earned her PhD from Harvard University under Yiling Chen’s supervision. Her research is supported by grants from Amazon, Google, MacArthur Foundation, and MIT’s GenAI Consortium.

Education: PhD in Computer Science (Harvard University, 2020), Diploma in Electrical & Computer Engineering (National Technical University of Athens, Greece). Key research areas include algorithmic economics, strategic learning, and mechanism design for online platforms. She has advised over 10 students across PhD, MBA, and undergraduate programs, emphasizing ethical and societal implications in her mentorship.

• Research Themes: Incentive-aware learning, strategic user interactions, fairness in algorithms, AI policy, and recommendation systems
• Awards: Amazon Research Award (2023), Google Faculty Award (2025), NeurIPS Spotlight Recognition (2023), AAAI Best Paper Shortlist (2019)

Her recent work explores how machine learning systems can be designed to account for human adaptation, including studies on recommendation systems, revenue management fairness, and causal mechanisms in strategic classification. She teaches courses on data modeling (15.060) and operations research (15.090) at MIT, blending theoretical rigor with practical industry applications.

Podimata’s interdisciplinary approach bridges computer science, economics, and management science, with publications in top venues like NeurIPS, EC, COLT, and ICML. She actively engages in policy discussions around AI governance through her research on algorithmic transparency and societal impacts.