Personal profile

Research interests

I am a Postdoctoral Research Associate, working with Prof. Samuel Kaski. My research experience lies in the following topics:

  1. Multi-Agent Reinforcement Learning
  2. Machine Learning for Smart Grids
  3. Interpretable Agent Decision Making

Currently, I am doing research in Ad Hoc Teamwork, i.e., solving a problem that how an agent collaborates with other unseen agents on the fly. My research tools to address this problem include: Game Theory, Causal Inference, and Graph Neural Networks. My vision is not only solving agent decision-making, but also pursuing interpretable decision-making process.

Biography

I obtained my Ph.D. degree from Imperial College London, UK, in 2024, under supervision of Dr. Yunjie Gu, Prof. Tim C. Green and Dr. Tae-Kyun Kim. Before that, I obtained my M.Res. degree from University College London (UCL), UK, with distinction, in 2018, under supervision of Prof. Jun Wang, as well as my M.Sc. degree from Imperial College London, UK, with merit, in 2017, under supervision of Prof. Björn Schuller for the master project. Earlier, I obtained my B.Eng. degree from University of Liverpool, UK, with the first-class honours degree, in 2016, under supervison of Prof. Danushka Bollegala and Prof. Karl Tuyls for the final year project.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 4 - Quality Education
  • SDG 5 - Gender Equality
  • SDG 7 - Affordable and Clean Energy
  • SDG 10 - Reduced Inequalities
  • SDG 11 - Sustainable Cities and Communities

Areas of expertise

  • QA75 Electronic computers. Computer science
  • Multi-Agent Systems
  • Machine Learning
  • Game Theory
  • Smart Grid
  • Causal Machine Learning

Research Beacons, Institutes and Platforms

  • Christabel Pankhurst Institute

Keywords

  • Multi-Agent Reinforcement Learning
  • Multi-Agent Systems
  • Game Theory
  • Causal inference

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