Research

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Preprints

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*, Aleksander Mądry*
pdf
In the media: Op-Ed at TIME, Science Magazine, Forbes, Fortune.

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
pdf

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

Can Users Fix Algorithms? A Game-Theoretic Analysis of Collective Content Amplification in Recommender Systems
Kat Fedorova, Madeline Celi Kitch, and Chara Podimata
pdf

Desirable Effort Fairness and Optimality Trade-offs in Strategic Learning
Valia Efthymiou, Kat Fedorova, and Chara Podimata
pdf

Online Scheduling for LLM Inference with KV Cache Constraints
Patrick Jaillet, Jiashuo Jiang, Konstantina Mellou, Marco Molinaro, Chara Podimata, and Zijie Zhou
pdf

Recommending to Strategic Users
Andreas Haupt, Dylan Hadfield-Menell, and Chara Podimata
pdf  slides  poster

Journal Publications

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

Conference Publications

2025

Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
In Proc. of the 39th conference on Neural Information Processing Systems (NeurIPS25)
Valia Efthymiou, Chara Podimata, Diptansghu Sen, and Juba Ziani
pdf

Contextual Dynamic Pricing with Heterogeneous Buyers
In Proc. of the 39th conference on Neural Information Processing Systems (NeurIPS25)
Thodoris Lykouris, Sloan Nietert, Princewill Okoroafor, Chara Podimata, and Julian Zimmert
pdf

2024

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

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

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)
Major Revision at Manufacturing and Service Operations Management (MSOM)
pdf

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

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

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

2023

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

Strategic Apple Tasting
Keegan Harris, Chara Podimata, and Zhiwei Steven Wu
In Proc. of the 37th conference on Neural Information Processing Systems (NeurIPS23)
pdf

2022

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

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

2021

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

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

2020

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

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

2019

A Bridge Βetween 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  poster  slides

2018

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

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

Expository

Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality
Chara Podimata
In SIGEcom Exchanges, Issue 22.2, March 2025
pdf

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

PhD Dissertation

Incentive-Aware Machine Learning for Decision Making
pdf