This are some project report samples!
PhD interview presentation for Imperial College Computing, covering research interests in cloud-edge collaborative AI inference. Topics include privacy-aware inference routing, distributed LLM deployment on heterogeneous edge devices, and system-level optimization for resource-constrained environments.
Evaluating LLMs (e.g., GPT-4o, LLaMA-3.3) in classic games such as Prisoner’s Dilemma, Ultimatum Game, and Public Goods Game. We propose a multi-agent routing framework PRIME-Router that improves strategic adaptability and persona consistency across repeated interactions.
Shield-MPPI combines sampling-based planning and safety enforcement through Control Barrier Functions (CBFs), enabling real-time, robust trajectory generation for autonomous racing on the F1TENTH platform. The system integrates EKF-based tracking, spline evasion planning, and a modular ROS2 architecture to ensure safety under dynamic racing conditions.
This undergraduate thesis proposes a two-phase optimization framework for solar-powered IoT networks, focusing on dynamic task allocation and energy-aware function configuration. A MILP benchmark and a GMM-enhanced Receding Horizon Control algorithm were developed to improve efficiency and adapt to fluctuating energy and computation conditions.