Design and implementation of an automated reinforcement learning framework. Benchmarked across various MuJoCo locomotion environments to evaluate performance and adaptability in continuous control tasks.

Developed a population-based meta-optimization algorithm that leverages swarm intelligence and Bayesian optimization to enhance hyperparameter tuning efficiency.

Applied advanced graph neural networks and RL algorithms to model and optimize dynamic network containment strategies under budget constraints.