Ph.D. in CS

Research & Initiatives
My research design and develop new algorithms and software architectures with provable properties in Multi-Agent Systems (MAS) and Multi-Robot Systems (MRS). Care about basic research that leads to fundamental new concepts can be simulated in AI agents or demonstrated on real robots and sensor networks.
Through these works, I was attracted by more challenging problems in MAS, MRS, Distributed Artificial Intelligence (DAI), and Swarm Intelligence. For example, probabilistic graphical models (PGM) in Bayesian Net inference and learning, modeling strategic by game-theoretic interactions, Deep Reinforcement Learning (DRL) extending from estimating agents' parameters and predicting their state, optimization algorithm design like the optimal actions of agent communication, planning & control.
Overview


Simulation & Hardware Demonstration
Explore Game with Greedy Algorithm in Robotarium
Pursuit-Evasion Game with Pure Pursuit (PP) Strategy on 1 vs 1 in Robotarium
Explore Game with GUT in Robotarium
Pursuit-Evasion Game with Constant Bearing (CB) Strategy on 1 vs 1 in Robotarium
Comparing CB, PP, and GUT under Pursuit-Evasion Game in Robotarium
