Upcoming Doctoral Dissertations

"Distributed multi-input multi-output (MIMO) RF sensing systems, which consist of multiple transmitters and receivers located at different positions, offer advantages such as higher spatial resolution, increased degrees of freedom, and enhanced target detection. However, practical deployment is challenged by asynchronous propagation paths, leading to synchronization errors, non-orthogonal waveforms, and the presence of both auto-correlation and cross-correlation terms at the matched filter (MF) output. This dissertation investigates these issues in realistic environments, focusing on asynchronous propagation, cross-correlation effects, and target detection under cluttered conditions." Read more...

"We investigate the applicability of Reinforcement Learning (RL) to portfolio optimization problems. Training RL agents for financial problems is challenging due to two primary issues 1) communication latency between traders and trading systems, which degrades performance, and 2) the need for a realistic market simulator for effective agent learning and interaction. Our three studies tackle these challenges. We further propose a hierarchical trading framework where two RL agents reinforce each other’s decisions through dynamically improving their respective utility functions" Read more...