1Georgia Tech students and postdocs are bolded.
2Conferences are the main publication venue for much of my research. All listed conferences are peer-reviewed and have competitive acceptance rates.
3Most papers are in alphabetical order.
4Papers while at Georgia Tech are denoted by a *
Preprints and Workshops
*Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
V. Efthymiou, C. Podimata, D. Sen, J. Ziani
*Multi-Agent Performative Prediction Beyond the Insensitivity Assumption: A Case Study for Mortgage Competition
G. Wang, K. Acharya, L. Lakshmikanthan, V. Muthukumar, J. Ziani
*Centralization vs Decentralization in Hiring and Admissions
B. Fish, D. Sen, J. Ziani
*On Rider Strategic Behavior in Ride-Sharing Platforms
J. Mulay, D. Sen, J. Ziani.
*Personalized Differential Privacy for Ridge Regression
K. Acharya, F. Boenisch, R. Naidu, J. Ziani.
Privacy Regulation and Protection workshop at ICLR 2024
*Randomized Quantization is All You Need for Differential Privacy in Federated Learning
Y. Yoon, Z. Hu, J. Ziani, and J. Abernethy.
Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities Workshop at ICML 2023.
Inference on Auctions with Weak Assumptions on Information
V. Syrgkanis, E. Tamer, and J. Ziani
Book Chapters
*Differential Privacy: Overview and Fundamental Techniques
F. Fioretto, P. V. Hentenryck, and J. Ziani
Chapter 1 of “Differential Privacy in Artificial Intelligence: From Theory to Practice”
Journal publications
*Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems
K. Acharya, V. Vangala, J. Wang, J. Ziani.
Transactions on Machine Learning Research (TMLR), 2025.
*The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition
G. Liao (co-first author), Y. Su (co-first author), J. Ziani, A. Wierman, J. Huang
Mathematics of Operations Research, 2023.
Conference and workshop versions below.
*Pipeline Interventions
E.R. Arunachaleswaran, S. Kannan, A. Roth, and J. Ziani
Mathematics of Operations Research, 2022.
Conference and workshop versions below.
Third-party Data Providers Ruin Simple Mechanisms
Y. Cai, F. Echenique, H. Fu, K. Ligett, A. Wierman, and J. Ziani
Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 2020
Conference version below
Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market
X. Ren, P. London, J. Ziani, and A. Wierman
IEEE/ACM Transactions on Networking 2018 (ToN)
Cliques in the union of graphs
R. Aharoni, E. Berger, M. Chudnovsky, and J. Ziani
Journal of Combinatorial Theory, Series B, 2015
Conference publications
*Differentially Private Data Release on Graphs: Inefficiencies and Unfairness
F. Fioretto, D. Sen, J. Ziani.
The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025.
*The Cost of Balanced Training-Data Production in an Online Data Market
A. Chaintreau, R. Maio, and J. Ziani
The International World Wide Web Conference (TheWebConf) 2025.
Algorithmic Fairness under the lens of Time (AFT) workshop at Neurips 2023.
*Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes
J. Ko, J. Ziani, S. Das, M. Williams, F. Fioretto.
Annual AAAI Conference on Artificial Intelligence (AAAI), 2025. Special track on AI for Social Impact.
*Algorithmic Collusion Without Threats
N. Collina, E.R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani.
Innovations in Theoretical Computer Science (ITCS), 2025.
*Equilibria of Data Marketplaces with Privacy-Aware Sellers under Endogenous Privacy Costs
D. Sen, J. Wang, J. Ziani.
IEEE Conference on Secure and Trustworthy Machine Learning (SATML), 2025.
International Conference on Algorithmic Decision Theory (ADT), 2024.
*Bayesian Strategic Classification
L. Cohen, S. Sharifi-Malvajerdi, K. Stangl, A. Vakilian, J. Ziani
Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.
*Oracle Efficient Algorithms for Groupwise Regret
K. Acharya, E. R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani
International Conference on Learning Representations (ICLR), 2024.
Optimization for Machine Learning (OPT) workshop at NeurIPS 2023.
*Sequential Strategic Screening
L. Cohen, S. Sharifi-Malvajerdi, K. Stangl, A. Vakilian, J. Ziani
International Conference on Machine Learning (ICML), 2023.
*Wealth Dynamics Over Generations: Analysis and Interventions
K. Acharya, E.R. Arunachaleswaran, S. Kannan, A. Roth, J. Ziani
IEEE Conference on Secure and Trustworthy Machine Learning (SATML), 2023.
*Optimal Data Acquisition with Privacy-Aware Agents
R. Cummings, H. Elzayn, V. Gkatzelis, E. Pountourakis, J. Ziani
IEEE Conference on Secure and Trustworthy Machine Learning (SATML), 2023.
Best Paper Award.
Talk available here.
*Information Discrepancy in Strategic Learning
Y. Bechavod, C. Podimata, Z.S. Wu, J. Ziani
International Conference on Machine Learning (ICML), 2022
NeurIPS 2021 workshop on Strategic Machine Learning
Short talk available here.
The Privacy Paradox and Optimal Bias-Variance Trade-offs in Data Acquisition
G. Liao, Y. Su, J. Ziani, A. Wierman, J. Huang
ACM Conference on Economics and Computation (EC), 2021
Algorithms and Learning for Fair Portfolio Design
E. Diana, T. Dick, H. Elzayn, M. Kearns, A. Roth, Z. Schutzman, S. Sharifi-Malvajerdi, and J. Ziani
ACM Conference on Economics and Computation (EC), 2021
Gaming Helps! Learning from Strategic Interactions in Natural Dynamics
Y. Bechavod, K. Ligett, Z. S. Wu, and J. Ziani
The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
NeurIPS workshop on Strategic Machine Learning
Workshop on Incentives in Machine Learning (IML) at the 2020 International Conference on Machine Learning (ICML)
Pipeline Interventions
E.R. Arunachaleswaran, S. Kannan, A. Roth, and J. Ziani
Innovations in Theoretical Computer Science (ITCS), 2021.
Appeared as an oral presentation at the Workshop on Mechanism Design for Social Good (MD4SG), 2020.
MD4SG talk available here
Differentially Private Call Auctions and Market Impact
E. Diana, H. Elzayn, M. Kearns, A. Roth, S. Sharifi-Malvajerdi, and J. Ziani
ACM Conference on Economics and Computation (EC), 2020
Third-party Data Providers Ruin Simple Mechanisms
Y. Cai, F. Echenique, H. Fu, K. Ligett, A. Wierman, and J. Ziani
ACM SIGMETRICS Conference on Measurement and Modeling of Computer Systems, 2020
Talk available here
Journal version above
Downstream Effects of Affirmative Action
S. Kannan, A. Roth, and J.Ziani
ACM Conference on Fairness, Accountability, and Transparency (FAccT, formerly known as FAT*), 2019
Talk available here
Access to Population-Level Signaling as a Source of Inequality
N. Immorlica, K. Ligett, and J. Ziani
ACM Conference on Fairness, Accountability, and Transparency (FAccT, formerly known as FAT*), 2019
Talk available here
Optimal Data Acquisition for Statistical Estimation
Y. Chen, N. Immorlica, B. Lucier, V. Syrgkanis, and J. Ziani
ACM Conference on Economics and Computation (EC), 2018
Talk available here
Non-Exploitable Protocols for Repeated Cake Cutting
O. Tamuz, S. Vardi, and J. Ziani
AAAI Conference on Artificial Intelligence (AAAI), 2018
Accuracy for Sale: Aggregating Data with a Variance Constraint
R. Cummings, K. Ligett, A. Roth, Z. S. Wu, and J. Ziani
Innovations in Theoretical Computer Science (ITCS), 2015
Other
*We Found the Best Shuffled Deck, a.k.a. “This is Not the Best Paper, no, this is Just a Tribute”
Tenacious Academics
SIGBOVIK 2024
Efficiently Characterizing Games Consistent with Perturbed Equilibrium Observations
V. Chandrasekaran, K. Ligett, and J. Ziani
Poster at the ACM Conference on Economics and Computation 2016 (EC)
Master’s thesis at Caltech