• April 2026: Our work titled "Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates" was accepted at the 43rd International Conference on Machine Learning (ICML 2026) .
• March 2026: Invited talk "Towards a Finite-Time Theory for Adversarially-Robust Reinforcement Learning" delivered at the CORAL Seminar, ECE Department, NCSU.
• January 2026: Our works titled "Robust Federated Q-Learning with Almost No Communication" and "Variance-Reduced Q-Learning for Static and Time-Varying Networks" were accepted for oral presentation and publication at the 2026 American Control Conference .
• October 2025: Presented a poster titled "Robust Federated Reinforcement Learning with Byzantine Agents" at the Applied AI Symposium 2025.
• September 2025: Our recent work titled "Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates" was accepted at the 39th Annual Conference on Neural Information Processing Systems (NeurIPS 2025), Reliable ML Workshop .
• September 2025: Our recent work titled "Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates" was released on arXiv. The work provides the first provably robust variants of asynchronous Q-Learning that tolerate adversarially corrupted rewards. The algorithm is distribution-agnostic and achieves near-optimal finite-time guarantees up to a provably unavoidable corruption term.
• September 2025: Poster "Adversarially-Robust TD Learning with Markovian Data" accepted at the New York Reinforcement Learning Workshop 2025, Amazon .
• April 2025: Passed my Ph.D. Oral Qualifying Examination! The committee members were my advisor Dr. Aritra Mitra (Assistant Professor, Department of ECE), Dr. Wenbin Lu (Professor, Director of Graduate Programs, Department of Statistics), Dr. Aranya Chakrabortty (IEEE Fellow, Professor, Associate Department Head for Research, Department of ECE), and Dr. Edgar Lobaton (Professor, Department of ECE).
• April 2025: Poster "Towards Finite-Time Rates for Adversarially-Robust Reinforcement Learning" accepted at the Northeast Systems and Control Workshop 2025, Columbia University .
• February 2025: Our extended preprint titled "Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits" was released on arXiv. To appear in the 28th International Conference on Artificial Intelligence and Statistics (AISTATS) 2025.
• January 2025: Our paper titled "Adversarially-Robust TD Learning with Markovian Data: Finite-Time Rates and Fundamental Limits" was accepted at the 28th International Conference on Artificial Intelligence and Statistics (AISTATS 2025) .
• December 2024: Presented our paper "Robust Q-Learning under Corrupted Rewards" at the 63rd IEEE Conference on Decision and Control 2024 in Milan, Italy.
• September 2024: Presented a poster titled "Robust Algorithms for Adversarial Reinforcement Learning" at the Applied AI Symposium, Theoretical Machine Learning Track.
• September 2024: Our extended preprint titled "Robust Q-Learning under Corrupted Rewards" was released on arXiv. To appear in the 63rd IEEE Conference on Decision and Control 2024.
• September 2024: Received the "IEEE CDC 2024 Student Travel Support Award".
• July 2024: Our paper titled "Robust Q-Learning under Corrupted Rewards" was accepted at the flagship 63rd IEEE Conference on Decision and Control 2024 .
• August 2023: Joined North Carolina State University, Raleigh, as a Ph.D. student under Dr. Aritra Mitra.
• July 2023: Graduated from the Indian Institute of Science, Bangalore, with an M.Tech. in Robotics and Autonomous Systems.
• February--March 2023: Received Ph.D. offers from North Carolina State University and Purdue University.