I am an Assistant Professor in the School of Industrial and Systems Engineering at Georgia Tech and a recipient of the NSF CAREER Award. My research and my students have also been supported by a Structural Democracy Fellowship from Moon Duchin’s MGGG lab, an internal IPAT grant, and an internal ARC-ACO Student Fellowship.
My research lies at the intersection of Computer Science, Operations Research, and Economics. I use tools from learning theory, game theory, and optimization to address technical and societal challenges arising from the rise of AI, ML, and data-driven decision making. I am particularly interested in:
1. The economics of data, in a world of exchanging data has become crucial to building powerful AI tools;
2. The privacy considerations from using larger and larger amounts of personal and sensitive data, with a focus on Differential Privacy;
3. The fairness considerations around AI, ensuring that algorithms and automated decision-making tools do not replicate human biases or introduce new biases;
4. The performance of ML models in high-stake environments when strategic user responses and distribution shifts are commonplace.
Before starting at Georgia Tech, I obtained a PhD in Computer Science from the Computing and Mathematical Science Department at Caltech, where I was advised by Adam Wierman and Katrina Ligett, in 2019. I was a Warren Center Postdoctoral Fellow in the Department of Computer and Information Science at the University of Pennsylvania from 2019 to 2021.
Recent News
- February 2025: Our paper on “Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems”, led by student author Krishna Acharya, has just been accepted at Transactions of Machine Learning Research (TMLR)!
- January 2025: Our paper on “Differentially Private Data Release on Graphs: Inefficiencies and Unfairness”, led by Sen, was just accepted at AISTATS 2025!
- January 2025: Our paper on “The Cost of Balanced Training-Data Production in an Online Data Market” has just been accepted at the WebConf 2025! With this work, we aim to advance the state of fairness in data transactions, noting that when data production incentives are taken into account, imposing fairness may not come at a cost anymore. Great job by the student lead author at Columbia on the paper, Roland Maio!
- January 2025: Teodora Baluta and I just received a “Structural Democracy Fellowship”, sponsored by Moon Duchin’s MGGG lab, for our joint project on “Data-Driven Democracy in Noisy and Adversarial Settings”!
- January 2025: Our work on Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes was just awarded an oral at AAAI-AISI! Congratulations Joonhyuk Ko on leading and doing incredible work on this!
- January 2025: Natalie Collina is speaking about our recent algorithmic collusion paper at ITCS; go check out her talk!
- December 2024: Congratulations to my student Sen for getting his work on “Equilibria of Data Marketplaces with Privacy-Aware Agents” accepted at SATML 2025!
- December 2024: Our work on Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes was just accepted at AAAI-AISI. This is joint work with Joonhyuk Ko, Saswat Das, Matt Williams, and Ferdinando Fioretto!
- December 2024: the first chapter of the new book on “Differential Privacy in Artificial Intelligence: From Theory to Practice” led by Nando Fioretto and Pascal Van Hentenryck is out! You can find the first chapter, co-authored by Nando Fioretto, Pascal Van Hentenryck, and myself here. Stay tuned for the full book to be published early 2025!
- December 2024: Congratulations to my student Sen for getting the Jerry & Harriett Thuesen PhD Fellowship for research excellence, recognizing two years and a half of great research in the areas of game theory and economic decision analysis!
- November 2024: Congratulations to my student Sen for getting the ARC-ACO Fellowship! Stay tuned for new work on the impact of Differential Privacy in congestion games and on how DP impacts bias and fairness.
- November 2024: I presented my line of work on building up towards more realistic models of strategic classification at the AIML seminar at the University of Virginia. This is based on two collaborations: one with Yahav Bechavod, Chara Podimata, Steven Wu; and one with Lee Cohen, Kevin Stangl, Saeed Sharifi-Malvajerdi, Ali Vakilian!
- November 2024: Our work on “Algorithmic Collusion without Threats” has just been accepted at ITCS 2025. This is joint work with Eshwar Ram Arunachaleswaran, Natalie Collina, and Aaron Roth at Penn.
- October 2024: my student Sen for presented his work on “Equilibria of Data Marketplaces with Privacy-Aware Agents” at both INFORMS 2024 and at the International Conference on Algorithmic Decision Theory (ADT) 2024. Congrats Sen on two great talks!
- August 2024: check out this new preprint by my student Sen on the bias and fairness implications of differentially private graph data release! This is joint work with Nando Fioretto at UVA.
- July 2024: Sen‘s paper on equilibria in data markets has been accepted at ADT 2024! It will appear in the proceedings as an extended one-page abstract.
- April 2024: Our lab was just awarded NSF CAREER! Check out our project on “Beyond Fair Algorithms: Mathematical Foundations for Long-Term Fairness with Humans in the Loop”