Talks and Presentations

Invited Talks

• “Federated On-Policy Reinforcement Learning,” Colloquium, Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, IN, March 2025.
• “Optimal Online Learning of Linear Inflation Rules under the Random Yield,” Purdue Operations Conference, West Lafayette, IN, August 2024.
• “Smoothed Robust Phase Retrieval,” Topic-Contributed Session on Advanced Statistical Methods in Nonparametric Statistics and Causal Inference for Complex Data Structures, Joint Statistical Meetings, Portland, OR, August 2024.

Poster Presentations

• “Robust Inference of Attributable Effects with Sensitivity Analysis for Stratified Observational Studies,” American Causal Inference Conference, Salt Lake City, April 2026.
• “Gap-Dependent Bounds for Federated Q-Learning,” The Forty-Second International Conference on Machine Learning (ICML), Vancouver, July 2025.
• “Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost,” 2025 C. R. and Bhargavi Rao Prize Conference, University Park, PA, May 2025.
• “Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition,” 2025 C. R. and Bhargavi Rao Prize Conference, University Park, PA, May 2025.
• “Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost,” The Thirteenth International Conference on Learning Representations (ICLR), Singapore, April 2025.
• “Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition,” Spotlight Poster Presentation, The Thirteenth International Conference on Learning Representations (ICLR), Singapore, April 2025.
• “Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost,” Penn State’s AI Week Research Forum, April 2025.
• “Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition,” Penn State’s AI Week Research Forum, April 2025.
• “Federated Q-Learning: Linear Regret Speedup and Low Communication Cost,” The Twelfth International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024.
• “Federated Q-Learning: Linear Regret Speedup and Low Communication Cost,” Penn State’s AI Week Research Forum, April 2024.
• “Smoothed Robust Phase Retrieval,” 2023 C. R. and Bhargavi Rao Prize Conference, University Park, PA, May 2023.
• “Smoothed Robust Phase Retrieval,” Statistical Foundations of Data Science and their Applications Conference, Princeton University, May 2023.
• “Smoothed Robust Phase Retrieval,” Modern Computation Statistics Workshop, University of Florida, January 2023.