Chentian Jiang

About Me

Hi! I’m Chentian and I’m currently a second-year Informatics PhD student supervised by Chris Lucas in the Lucas Lab, University of Edinburgh.

I am excited about topics in Computational Cognitive Science: my research aims to build computational models that employ human-like learning strategies, with a focus on causal learning and transfer learning. People are skilled at choosing actions to discover the causal relationships in their environment, including the abstract properties of these relationships that transfer to new situations. By studying their choices, I am interested in integrating human strategies into computational solutions for causal learning problems.

Previously, I worked in Data Science at Uptake (Chicago startup) and studied at Duke University, where I completed my BSc in Computer Science and researched biomedical wearable devices in the Big Ideas Lab.

email | google scholar | github | linkedin


Education

PhD Informatics, 2023 (ongoing)
ILCC, University of Edinburgh
I am grateful to be funded by:

BSc Computer Science, 2019
Minor Neuroscience
Duke University


Publications

Lucas Lab

 (University of Edinburgh)

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


Big Ideas Lab

 (Duke University)

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 ]


Talks

Causal meta-learning by making informative interventions about the functional form.
Chentian Jiang, Christopher Lucas
1-Page Abstract at the 16th Workshop for Women in Machine Learning at NeurIPS 2021 Selected as an outstanding abstract to be featured as a contributed talk.