We welcome a new postdoctoral associate, Hongjiang Qian, to our lab. Hongjiang recently received his Ph.D. in mathematics at the University of Connecticut under Prof. George Yin. His research expertise is in stochastic approximation, stochastic PDEs, and large deviations theory.
TMLR Acceptance
Adit’s work ‘Controlling Federated Learning for Covertness‘ has been accepted to the Transactions of Machine Learning Research. Congratulations!
Kunal and Rui Graduate
We congratulate Kunal Pattanayak and Rui Luo for graduating and earning their PhDs! Rui will start an assistant professorship position at the City University of Hong Kong in China, and Kunal will begin working as a risk strategist at Goldman Sachs in New York.
2023 ICASSP Papers Accepted
We are happy to announce that our papers ‘Adaptive ECCM for Mitigating Smart Jammers‘ (K. Pattanayak, S. Jain, V. Krishnamurthy, C. Berry) and ‘Identifying Coordination in a Cognitive Radar Network–A Multi-Objective Inverse Reinforcement Learning Approach‘ (L. Snow, V. Krishnamurthy, B.M. Sadler) have been accepted to the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
2022 CDC Papers Accepted
Our recent paper ‘Lyapunov based Stochastic Stability of Human-Machine Interaction: A Quantum Decision System Approach‘ has been accepted for publication in, and presentation at, the proceedings of the 2022 IEEE Conference on Decision and Control (CDC). The authors are Shashwat Jain, Luke Snow, and Prof. Vikram Krishnamurthy. Our group’s second paper ‘Inverse-Inverse Reinforcement Learning. How to Hide Strategy from an…