I am a PhD in Computer Science at the University of Oxford, supervised by Prof. Michael Wooldridge and Prof. Alex Rogers . My research interests include Multiagent Reinforcement Learning, Hierarchical Reinforcement Learning and Game Theory. In particular, my thesis studies Game-theoretic Payoff Allocation in Multiagent Machine Learning Systems.
Prior to my PhD, I obtained an MSc in Computer Science (Graduated with Distinction, 2016) from the University of Oxford. I obtained a BSc in Physics with a Minor Degree in IT (First class honours, 2015) from the Hong Kong University of Science and Technology. I was an exchange student at EPFL (Spring 2014).
During my PhD, I was a Research Intern at Microsoft Research Cambridge (Summer 2019) where I was supervised by Dr. Sebastian Tschiatschek. I was a Machine Learning Intern at Apple Siri Cambridge (Summer 2017) where I was supervised by Dr. Thomas Voice.
|Jul 11, 2022||Paper accepted at IEEE Transactions on Artificial Intelligence: Replication Robust Payoff Allocation in Submodular Cooperative Games|
|Jul 1, 2022||New Affiliation: I will be joining Amazon as an Applied Scientist in the Personalization team.|
|May 14, 2022||Paper accepted at IJCAI’22 (Long Oral): Option Transfer and SMDP Abstraction with Successor Features|
|Feb 11, 2022||PhD ThesisThesis Defended!|
|Dec 20, 2021||Paper accepted at AAMAS’22 (Oral): Multiagent Model-based Credit Assignment for Continuous Control. Granted scholarship for attending the AAMAS’22 Conference.|
AAMAS’22Multiagent Model-based Credit Assignment for Continuous ControlIn The 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2022
IJCAI’22Option Transfer and SMDP Abstraction with Successor FeaturesThe 31st International Joint Conference on Artificial Intelligence 2022
OxfordGame-theoretic payoff allocation in multiagent machine learning systems2021
IEEE TAIReplication Robust Payoff Allocation in Submodular Cooperative GamesIEEE Transactions on Artificial Intelligence 2022
Inf. Comput.Behavioural strategies in weighted Boolean gamesInformation and Computation 2021
AAMAS’19Multi-Agent Hierarchical Reinforcement Learning with Dynamic TerminationIn Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems 2019