Themes

The research activities of our lab focusses on the theoretical foundations of machine intelligence and its applications to a variety of real-world problems.

Current areas of interest include:

  • Theory and applications of machine learning;
  • Generative AI (foundational models/large language models and their applications);
  • Multi-agent reinforcement learning systems;
  • Cooperation and coordination in multi-agent systems (cooperative AI);
  • AI and game theory;
  • Moral decision-making in AI systems;
  • Graph neural networks, graph reinforcement learning and their applications of machine learning to networks;
  • Causal reinforcement learning;
  • Human-AI interaction;
  • AI and society.
  • AI safety;
  • Machine intelligence for mobile, IoT and cyber-physical systems;
  • Machine intelligence for distributed and networked systems;
  • Machine intelligence for security&privacy.


Last updated: 28 January 2024.