Chentian Jiang

Chentian Jiang is a PhD student at the University of Edinburgh, specializing in Informatics. He is currently supervised by Chris Lucas and Edoardo Ponti. His research focuses on reinforcement learning, causality, and meta-learning, particularly how these concepts apply to both human and artificial agents. Jiang's work aims to understand how agents can learn causal relationships in their environments, which can enhance the development of more effective reinforcement learning models.12

Education and Background

• PhD in Informatics (Expected Completion: May 2025)
  University of Edinburgh
• BSc in Computer Science (2019)
  Duke University, with a minor in Neuroscience

Research Experience

Chentian is currently a Research Intern on the Game Intelligence team at Microsoft Research, where he is mentored by Tabish Rashid. Previously, he interned as a Research Scientist at DeepMind, working with the Reinforcement Learning team led by David Silver and mentored by Hado van Hasselt.12

Publications

Jiang has contributed to several notable publications, including:

• "Actively Learning to Learn Causal Relationships" - Computational Brain & Behavior, 2024
• "Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration" - Best paper at ICLR 2023
• "Causal meta-learning by making informative interventions about the functional form" - Featured talk at NeurIPS 2021

Additional Information

Chentian Jiang is actively involved in research that bridges cognitive science and artificial intelligence. His work is supported by scholarships such as the Principal’s Career Development Scholarship and the Edinburgh Global Research Scholarship.1 You can find more about him on his LinkedIn profile or his personal website.13