About Me

Hi! I’m Chentian. I grew up in Norway and am pursuing an Informatics PhD at the University of Edinburgh, where I am supervised by Chris Lucas and Edoardo Ponti.

During my PhD, I completed a Research Scientist Internship at DeepMind (Reinforcement Learning team led by David Silver), where I was mentored by Hado van Hasselt.

My research interests are in reinforcement learning, causality, and generalization/meta-learning. I explore these topics in both human and artificial agents: People are skilled at choosing actions to discover the causal relationships in their environment, including the abstract properties of these relationships that help them learn faster in new situations. How can we develop a model/theory to understand their choices? How can we leverage this understanding to build better artifical agents, especially reinforcement learning agents? These questions are core to my research.

Before starting my PhD, I worked in Data Science at Uptake (Chicago startup) and studied at Duke University, where I completed my Computer Science BSc with a Neuroscience minor and researched biomedical wearable devices in the Big Ideas Lab.

email | google scholar | github | linkedin

Education

PhD Informatics, Expected End Date: Dec. 2024
ILCC, University of Edinburgh
I am grateful to be funded by:

Principal’s Career Development Scholarship
Edinburgh Global Research Scholarship

BSc Computer Science, 2019
Minor Neuroscience
Duke University

Publications

Actively Learning to Learn Causal Relationships
Chentian Jiang, Christopher G. Lucas
Computational Brain & Behavior, 2024
[ pdf ] [ preregistration 1 ] [ preregistration 2 ]

Learning How to Infer Partial MDPs for In-Context Adaptation and Exploration
Chentian Jiang, Nan Rosemary Ke, Hado van Hasselt
Reincarnating RL Workshop at ICLR 2023
Neurosymbolic AI for Agent and Multi-Agent Systems Workshop at AAMAS 2023 - Best paper
[ pdf ] [ poster ]

Causal meta-learning by making informative interventions about the functional form
Chentian Jiang, Christopher G. Lucas
Women in Machine Learning Workshop at NeurIPS 2021 - Outstanding abstract and featured as a talk (click the “SlidesLive Video” button under “Chentian Jiang”)

Exploring Causal Overhypotheses in Active Learning
Chentian Jiang, Christopher G. Lucas
In Proceedings of the Annual Meeting of the Cognitive Science Society 2021
[ pdf ] [ poster ] [ preregistration ] [ 3min video summary ]

Pre-PhD

The Digital Biomarker Discovery Pipeline: An open source software platform for the development of digital biomarkers using mHealth and wearables data
Brinnae Bent, Ke Wang, Emilia Grzesiak, Chentian Jiang, Yuankai Qi, Yihang Jiang, Peter Cho, Kyle Zingler, Felix Ikponmwosa Ogbeide, Arthur Zhao, Ryan Runge, Ida Sim, Jessilyn Dunn
2020 Journal of Clinical and Translational Science
[ link ] [ pdf ]

Estimating Personal Resting Heart Rate from Wearable Biosensor Data
Chentian Jiang, Lida Faroqi, Latha Palaniappan, Jessilyn Dunn
2019 IEEE BHI
[ link ]