Research Areas

Our team at the Department of Data and Systems Engineering, The University of Hong Kong, specializes in Learning for Sequential Decision-Making and Continuous Control.

We are particularly interested in advancing the following research areas:

• Theoretical foundations, algorithm design, and applications of (Multi-agent) Reinforcement Learning;
• Developing a unified theoretical framework for Reinforcement Learning, Optimal Control, and Stochastic Optimization;
• Scaling Laws in sequential decision-making, with a special emphasis on efficient (Multi-agent) Monte Carlo Tree Search algorithms and advanced Reasoning Models;
• Robotic Foundation Models;
• End-to-end multi-modal learning for Humanoid Robotic Control and its industrial applications;
• Post-training techniques for Large Language Model agents and their applications in sequential decision-making;
• Artificial General Intelligence grounded in the principles of The Alberta Plan.

How to join us

Current Openings
(If interested, please contact Dr. Jiayu Chen directly. The Ph.D. application system accepts submissions year-round.)

• Fully funded Ph.D. positions starting in Fall 2025 have been taken.
• Openings for self-financed Ph.D. students and research assistants are available year-round.
• ❗❗❗ We have an available postdoc position in reinforcement learning and robotic learning.
• ❗❗❗ We need a remote research intern for a project to benchmark offline RL and control methods for plasma control in nuclear fusion. Please check this repo for details and reach out to Dr. Jiayu Chen if interested.

Qualifications for Ph.D. and Postdoctoral Researchers:
Candidates should possess strong proficiency in mathematics or programming, as well as demonstrate self-motivation and resilience. Applicants with backgrounds in the following areas are highly preferred: Humanoid Robots, Large Language/Reasoning Models, Control Theory, Optimization Theory, Statistical Machine Learning.

For more information, please refer to the respective categories in openings.