Research

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Preprints

Conformal Language Modeling via Posterior Sampling
Nicolas Emmenegger, Theo X. Olausson, Armando Solar-Lezama, and Chara Podimata
pdf
AI safetyUncertainty Quantification
Prediction-Powered Inference Across Many Tasks for AI Evaluation & Social Science Research
Nicolas Emmenegger, Ellery Stahler, and Chara Podimata
pdf
AI auditingAI Evaluation
Large Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season
Sarah H. Cen, Andrew Ilyas, Hedi Driss, Charlotte Park, Aspen Hopkins, Chara Podimata, and Aleksander Mądry
Featured in TIME (Op-Ed) Science Forbes Fortune
pdf
AI auditingAI Evaluation
Do LLMs Track Public Opinion? A Multi-Model Study of Favorability Predictions in the 2024 U.S. Presidential Election
Riya Parikh, Sarah H. Cen, Chara Podimata
pdf
AI auditingAI Evaluation
Can Users Fix Algorithms? A Game-Theoretic Analysis of Collective Content Amplification in Recommender Systems
Kat Fedorova, Madeline Celi Kitch, and Chara Podimata
pdf
Societal Impacts of AIIncentive-aware AI
Online Scheduling for LLM Inference with KV Cache Constraints
Patrick Jaillet, Jiashuo Jiang, Konstantina Mellou, Marco Molinaro, Chara Podimata, and Zijie Zhou
pdf
Online learning
Recommending to Strategic Users
Andreas Haupt, Dylan Hadfield-Menell, and Chara Podimata
pdf slides poster
Societal Impacts of AIIncentive-aware AI

Journal Publications

Density-Based Algorithms for Corruption-Robust Contextual Search and Convex Optimization
Renato Paes Leme, Chara Podimata, and Jon Schneider
Mathematics of Operations Research, 2026 (MOR26)
pdf slides
Online learning
Contextual Search in the Presence of Adversarial Corruptions
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire
Operations Research, 2022 (OR22)
pdf slides video poster
Online learning

Conference Publications

Automating Auditing of Personalization Systems at Scale with Large Language Models
Alessandro Morosini, Sarah H. Cen, Andrew Ilyas, Hedi Driss, Aleksander Mądry, and Chara Podimata
In Proc. of the 27th ACM Conference on Economics and Computation (EC26)
pdf
AI auditingAI Evaluation
Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
Valia Efthymiou, Kat Fedorova, and Chara Podimata
In Proc. of the 43rd International Conference on Machine Learning (ICML26)
pdf
Incentive-aware AISocietal Impacts of AI
Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
Valia Efthymiou, Chara Podimata, Diptansghu Sen, and Juba Ziani
In Proc. of the 39th conference on Neural Information Processing Systems (NeurIPS25)
pdf
Societal Impacts of AIIncentive-aware AI
Contextual Dynamic Pricing with Heterogeneous Buyers
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor, Chara Podimata, and Julian Zimmert
In Proc. of the 39th conference on Neural Information Processing Systems (NeurIPS25)
pdf
Online learningMechanism design
Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions
Nivasini Ananthakrishnan, Nika Haghtalab, Chara Podimata, and Kunhe Yang
In Proc. of the 38th conference on Neural Information Processing Systems (NeurIPS24)
pdf
Incentive-aware AI
When Should you Offer an Upgrade: Online Upgrading Mechanisms for Resource Allocation
Patrick Jaillet, Chara Podimata, Andrew Vakhutinsky, and Zijie Zhou
In Proc. of the 20th conference on Web and Internet Economics (WINE24)
pdf
Mechanism design
Grace Period is All You Need: Individual Fairness without Revenue Loss in Revenue Management
Patrick Jaillet, Chara Podimata, and Zijie Zhou
In Proc. of the 20th conference on Web and Internet Economics (WINE24)
pdf
Mechanism design
Preferences Evolve And So Should Your Bandits: Bandits with Deterministically Evolving Preference Effects
Khashayar Khosravi, Renato Paes Leme, Chara Podimata, and Apostolis Tsorvantzis
In Proc. of the 25th conference on Economics and Computation (EC24)
pdf
Online learningSocietal Impacts of AI
Can Probabilistic Feedback Drive User Impacts in Online Platforms?
Jessica Dai, Bailey Flanigan, Meena Jagadeesan, Nika Haghtalab, and Chara Podimata
In Proc. of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS24)
pdf
Societal Impacts of AIOnline learning
Strategyproof Decision-Making in Panel Data Settings and Beyond
Keegan Harris, Anish Agarwal, Chara Podimata, and Zhiwei Steven Wu
In ACM SIGMETRICS Performance Evaluation Review 2024 (SIGMETRICS24)
pdf
Incentive-aware AIMechanism design
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
Nika Haghtalab, Chara Podimata, and Kunhe Yang
In Proc. of the 37th conference on Neural Information Processing Systems (NeurIPS23)
Spotlight
pdf
Incentive-aware AIOnline learningUncertainty Quantification
Strategic Apple Tasting
Keegan Harris, Chara Podimata, and Zhiwei Steven Wu
In Proc. of the 37th conference on Neural Information Processing Systems (NeurIPS23)
pdf
Incentive-aware AIOnline learning
Corruption-Robust Contextual Search through Density Updates
Renato Paes Leme, Chara Podimata, and Jon Schneider
In Proc. of the 35th Annual Conference on Learning Theory (COLT22)
pdf slides
Online learning
Information Discrepancy in Strategic Learning
Yahav Bechavod, Chara Podimata, Zhiwei Steven Wu, and Juba Ziani
In Proc. of the 39th International Conference on Machine Learning (ICML22)
pdf slides poster
Incentive-aware AISocietal Impacts of AI
Adaptive Discretization for Adversarial Lipschitz Bandits
Chara Podimata and Alex Slivkins
In Proc. of the 34th Annual Conference on Learning Theory (COLT21)
pdf slides video poster
Online learning
Contextual Search in the Presence of Irrational Agents
Akshay Krishnamurthy, Thodoris Lykouris, Chara Podimata, and Robert Schapire
In Proc. of the 53rd ACM Symposium on Theory of Computing (STOC21)
pdf slides video poster
Online learning
Learning Strategy-Aware Linear Classifiers
Yiling Chen, Yang Liu, and Chara Podimata
In Proc. of the 34th Conference on Neural Information Processing Systems (NeurIPS20)
pdf poster
Incentive-aware AI
No-Regret and Incentive-Compatible Online Learning
Rupert Freeman, David M. Pennock, Chara Podimata, and Jennifer Wortman Vaughan
In Proc. of the 37th International Conference on Machine Learning (ICML20)
pdf slides video poster
Online learningMechanism designIncentive-aware AI
A Bridge Between Liquid and Social Welfare in Combinatorial Auctions with Submodular Bidders
Dimitris Fotakis, Kyriakos Lotidis, and Chara Podimata
In Proc. of the 33rd AAAI Conference on Artificial Intelligence (AAAI19)
pdf slides poster
Mechanism design
Strategyproof Linear Regression in High Dimensions
Yiling Chen, Chara Podimata, Ariel D. Procaccia, and Nisarg Shah
In Proc. of the 19th ACM Conference on Economics and Computation (EC18)
Among the 5 shortlisted papers for the Best Paper Award (EC18).
pdf slides video poster
Incentive-aware AIMechanism design
Learning to Bid without Knowing your Value
Zhe Feng, Chara Podimata, and Vasilis Syrgkanis
In Proc. of the 19th ACM Conference on Economics and Computation (EC18)
Spotlight award — 2nd place prize at the 13th Annual ML Symposium (NYAS).
pdf github slides poster
Online learningMechanism design

Expository

Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality
Chara Podimata
In SIGEcom Exchanges, Issue 22.2, March 2025
pdf
Incentive-aware AI
Strategyproof Linear Regression in High Dimensions: an Overview
Yiling Chen, Chara Podimata, Ariel D. Procaccia, and Nisarg Shah
In SIGEcom Exchanges, Issue 17.1, April 2019
pdf
Incentive-aware AIMechanism design

PhD Dissertation

Incentive-Aware Machine Learning for Decision Making
Chara Podimata
pdf
Incentive-aware AI