I lead the MINDS lab, where we study decision making and learning in networks (including network games, multi-agent reinforcement learning, and learning for optimization in networks/graphs), and the ethics and economics of AI (including data biases, algorithmic fairness, and strategic human-in-the-loop). Our research has been generously supported by the National Science Foundation, Amazon, and Cisco.
Recent News
- June 2026: Our paper "Fair Robust Strategic Classification under Decision-Dependent Cost Uncertainty" led by Sura has been accepted in the NExt-Game@ICML'26 workshop. Congratulations, Sura!
- June 2026: Our paper "The Double-Edged Sword of Information: Revealed versus Hidden Lotteries in School Choice" together with Jingyan Wang has been accepted at the 3rd Workshop on New Directions in Social Choice at EC 2026.
- April 2026: Our paper "Test-Time Adaptation for Unsupervised Combinatorial Optimization" led by Yiqiao has been accepted to the Transactions on Machine Learning Research (TMLR). Congratulations, Yiqiao!
- April 2026: Our paper "Robust Strategic Classification under Decision-Dependent Cost Uncertainty" led by Sura has been accepted in ICML (~26.6% acceptance rate). Congratulations, Sura!
- March 2026: Parinaz gave an invited talk on "Bias and Uncertainty in Strategic Machine Learning" at GameNets 2026.