Available Research Positions at the Agentic Intelligence Lab @ The University of Hong Kong
About the PI
Jiayu Chen (陈佳玉) is an incoming Tenure-Track Assistant Professor at the Department of Data and Systems Engineering, The University of Hong Kong. Currently, he is a Postdoctoral Fellow at the School of Computer Science, Carnegie Mellon University, working under the supervision of Professor Jeff Schneider on data-driven profile control for nuclear fusion, as part of a joint research program with the Plasma Control Group, Princeton University.
Dr. Chen earned his Ph.D. in Industrial Engineering and Operations Research from the Edwardson School of Industrial Engineering, Purdue University and a Bachelor of Engineering from the College of Engineering, Peking University. During his Ph.D., he was co-advised by Professor Vaneet Aggarwal (Purdue University), an expert in theoretical reinforcement learning, and Professor Tian Lan (George Washington University), an expert in multi-agent systems.
He is the director of the Agentic Intelligence Lab, where his research focuses on Learning for Sequential Decision-Making and Continuous Control. Dr. Chen has published extensively in top venues such as NeurIPS, ICML, ICRA, ICAPS, AAMAS, TMLR, and IEEE TNNLS as the first author. His work has been recognized with prestigious awards, including the Oracle Research Award and the Purdue Research Grant.
About the University/Department
Founded in 1911, the University of Hong Kong (HKU) is the oldest tertiary education institution in Hong Kong, renowned globally for its excellence in teaching, research, and innovation. According to the QS World University Rankings, HKU is currently ranked 2nd in Asia and 17th worldwide. Studying at HKU offers unique advantages: its location in the vibrant, internationally connected city of Hong Kong provides unmatched access to global business networks, a multicultural environment, and close proximity to the thriving economies of the Greater Bay Area.
In the midst of the artificial intelligence and big data revolution, the Department of Data and Systems Engineering (DASE) upholds the philosophy of “computing-in-practice”. The vision is to bridge the cyber and physical worlds by integrating data science methodologies, such as artificial intelligence, with human tools like robots to create greater value for humanity. To achieve this goal, DASE focuses on three key areas: Data Engineering and Analytics, Human-Machine Cooperation, and Robotics and Automation.
Research Areas
The Agentic Intelligence Lab conducts broad research across Machine Learning, Robotics, and Operations Research. At present, our work focuses on advancing the following key 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.
Available Positions
We have the following openings:
- Two fully funded Ph.D. positions starting in Fall 2025 (as early as July)
- Openings for postdoctoral researchers, self-financed Ph.D. students, part-time Ph.D. students, research assistants, and visiting scholars are available year-round
Ph.D. and postdoctoral applicants are expected to have strong proficiency in mathematics or programming, along with demonstrated self-motivation and resilience. Candidates with expertise in the following areas are highly preferred: Humanoid Robots, Large Language/Reasoning Models, Control Theory, Optimization Theory, Statistical Machine Learning.
We offer competitive remuneration. For Ph.D. students, the basic level of scholarship is 18,760 HK dollars per month. For postdocal researchers, the basic salary is no less than 30,000 HK dollars per month. Outstanding candidates are encouraged to apply for the HKU Presidential PhD Scholar Programme (HKUPS), Hong Kong PhD Fellowship Scheme (HKPFS), and RGC Postdoctoral Fellowship Scheme (PDFS) to get financial support of approximately 430,000 HK dollars annaly.
We also provide opportunities for visiting experiences at top U.S. universities such as UC Berkeley, UIUC, CMU, Purdue, and GWU. For research assistants, we offer strong recommendation letters and ample opportunities to publish papers in top machine learning and robotics venues.
For detailed requirements and additional information, please refer to the respective categories in openings. If interested, please contact Dr. Jiayu Chen directly through jiayuchen98666@gmail.com or jiayuc2@andrew.cmu.edu. The Ph.D. application system at HKU accepts submissions year-round.
Deeply sorry that I am unable to respond to every inquiry unless it is to send an interview invitation.