Welcome

We have multiple positions available at the levels of PhD students (admission in September 2026, January/September 2027), Postdoctoral Fellows and Research Assistant at Lingnan University (Hong Kong SAR). Please check Join Us for more details.

Research Group

I’m leading the Learning and Optimisation in Games (LOG) Group under the Nature Inspired Computation and Applications Laboratory (NICAL).

Research Interests

For more about our research, please check our Group website or my publications on Google Scholar. My Erdös Number is 4, through Sylvie Ruette, Bernard Host and Vitaly Bergelson.

• AI in/for Games
  • Procedural Content Generation (PCG): Leveraging deep learning (DL), reinforcement learning (RL), evolutionary computation (EC) and large language models (LLMs) to automatically and adaptively create novel and diverse video game levels, rules, and scenarios.
  • AI for Game-Playing: Developing advanced algorithms (particularly EC-based and RL-based) for autonomous game agents: general game playing (GGP), general video game playing (GVGP), autonomous racing.
  • AI in Education & Educational Games: Researching methods to turn digital games into interactive tools that maximise learning efficiency and revolutionize CS/AI education.
• Learn to Optimise under Uncertainty
  • Algorithm Portfolios & MetaBBO: Designing automated configurations for black-box optimisers (Meta-Black-Box Optimisation) to reduce human engineering effort.
  • Dynamic Multi-Objective Optimisation: Researching how evolutionary algorithms can adapt to changing environments while balancing multiple conflicting objectives, and improve generalisation and robustness.
• Smart Logistics
  • Vehicle Routing & Material Handling: Developing neural solvers for the vehicle routing problem (VRP) variants and dynamic scheduling systems for real-world manufacturing and smart factory logistics.
  • Autonomous Driving: Generating controllable, multimodal driving scenarios and motion patterns to rigorously stress-test autonomous driving systems (ADSs) and virtual racing simulators.
• Fair Machine Learning & AI Ethics
  • Algorithmic Fairness & Robustness: Developing trustworthy AI frameworks that guarantee fair downstream decision-making processes and outcomes in stationary or non-stationary environments characterised by data imbalance, concept drift, and environmental uncertainty.
  • Ethical Concerns in LLMs: Investigating hidden biases/discrimination when LLMs are deployed in multiplayer environments like the game Werewolf (Mafia).

Grants

PI of projects funded by MOST, NSFC, Guangdong Science and Technology Department, Shenzhen Science and Technology Innovation Commission, etc., and industrial partners, such as Tencent.

Professional Experience

• Present, Associate Professor
  Head of Learning and Optimisation in Games (LOG) Group
  School of Data Science (SDS), Lingnan University, Hong Kong SAR, China
• 2024-2027, Honorary Research Associate
  School of Engineering and Computer Science, Victoria University of Wellington, New Zealand
• 2021-2024, Tenure-Track Assistant Professor
  Head of Learning and Optimisation in Games (LOG) Group
  Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China
• 2018-2021, Research Assistant Professor/Research Associate Professor
  Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China
• 2017-2018, Postdoc
  Collaborated PI: Simon Lucas (Professor of Artificial Intelligence, Head of Game AI Research Group, Head of School)
  School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), UK
• 2016-2017, Postdoc
  Collaborated PI: Simon Lucas (Professor, Head of School)
  School of Computer Science and Electronic Engineering, University of Essec (UoE), UK

Education

• 2016, Ph.D in Computer Science
  Portfolio methods in uncertain contexts (in English)
  Team TAO, INRIA Saclay-CNRS-LRI, Université Paris-Saclay, Paris Saclay, France
  Supervisors: Olivier Teytaud (INRIA Saclay / Google Brain / Meta AI) and Marc Schoenauer (Deputy Research Director at INRIA, in charge of AI, INRIA Saclay)
  Examined by Bruno Bouzy, Philippe Dague, Marcus Gallagher, Simon Lucas, Petr Pošík and Günter Rudolph.
• 2013, Master’s degree in Bioinformatics and Biostatistics Reconstruction of molecules with new functions using artificial simulations by directed evolution (in French)
  BIOcomputing and Structure (BIOS) Research Group, École Polytechnique & Université Paris-Sud, Orsay, France
  Supervisors: Jérôme Azé, Thomas Simonson and Thomas Gaillard
• 2012, Engineer’s degree in Computer Science (Network, Artificial Intelligence)
  Polytech’Paris-Sud, Orsay, France
• 2010, Bachelor’s degree in Optical & Electronic Information
  School of Optical and Electronic Information, Huazhong University of Science and Technology (HUST), Wuhan, China

Invited Talks

• Keynote at the 2025 Advances in Computer Games Conference (ACG 2025) (online), 23 October 2025.
• Invited talk at Leiden University (Maastricht, Netherlands), 27 February 2025.
• Keynote at the 2024 IEEE World Congress on Computational Intelligence (Yokohama, Japan), 4 July 2024.
• Invited talk at University of Malta (Malta), 23 November 2023.
• Invited lecture at University of Málaga (online), 27 May 2022.
• Invited talk at ByteDance (Shenzhen, China), 15 April 2021.
• Invited lecture at 2020 IEEE Biennial Congress of Argentina (online), 4 December 2020.
• Invited talk at French Platform on Artificial Intelligence (online), 1 July 2020.
• Invited talk at Tencent (Shenzhen, China), 27 July 2018.
• Invited talk at Google DeepMind (London, UK), 7 March 2018.
• Invited talk at Maastricht University (Maastricht, Netherlands), November 2017.