Published several papers on data sharing incentive mechanisms, such as 'A Cramér-von Mises Approach to Incentivizing Truthful Data Sharing' (NeurIPS 2025), 'Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution' (ICML 2025), etc.
Research Experience
One of the current research agendas is exploring the incentives that arise when agents share data with one another. Developing data-sharing mechanisms and marketplaces that promote truthful data contribution, ensure fair benefits for the participants, and generate value for society as a whole.
Education
Previously at UC Berkeley, Carnegie Mellon University, and the University of Moratuwa, Sri Lanka.
Background
Assistant Professor, working on theoretical topics in machine learning and game theory.
Miscellany
Currently teaching CS/ECE/STAT-861 - Theoretical Foundations of Machine Learning at UW-Madison. Recruiting students with strong backgrounds in mathematics and statistics.