Trustworthy AI Lab

Founded since 2019, the Trustworthy AI Lab is dedicated to improving the robustness, adaptability, and explainability of neural learning systems in the wild. A key focus of our work is trustworthy transfer learning through the study of transferability estimation.

See the Research Page to learn more.

Group Photo

For Perspective MS/PhD Students

[Update]

Starting 2026, I am no longer recruiting at Tsinghua SIGS as I will be joining School of AI (SAI) at Chinese University of Hong Kong at Shenzhen. MS/PhD positions (for class of Fall 2026 or later) at SAI are available! See the links below for more information about the program:

If you are emailing me to inquire about your graduate application for the first time, please also include a coding project sample (e.g. github repository link) and an English writing sample (e.g. a scientific paper or a project report).

Requirements

  • Highly motivated students interested in impactful machine learning and AI research

  • CS/EE or STEM background with CS training

  • Bonus: Dedicated research experience in a particular field (quality > quantity)

  • Bonus: Hands on experience of developing efficient AI/software system

Postdoc Position

I'm currently looking for a postdoc researcher to join our group. Potential research topics:

  • Lifelong neural learning systems for safety critical tasks

  • Reliable and interpretable reasoning for medical images and clinical AI

The ideal candidate should have a Ph.D. degree with experience in machine learning (e.g. especially if you are interested in reliable, explainable machine learning) or a background in medical image processing with hands-on experience of working with large-scale medical data.

Graduated Students

Ph.D.

  • Spring 2025: Xiangyu Chen (Huawei 2012 Lab)

  • Spring 2024: Taurai Muvunza (Queen Mary University of London)

  • Spring 2023: Yang Tan (Baidu)

Masters

  • Spring 2025: Jiahao Lai (Ph.D. at University of Hongkong), Peiwen Li (Ph.D. at Yale), Chengfeng Wu (Ph.D. at Tsinghua SIGS), Shutong Duan (China Telecom), Jie Min (Organization Department of Hangzhou)

  • Spring 2024: Qiqi Chen (UNIDO), Dexu Kong (Tencent), Zhiyuan (China Telecom Cloud), Shutong Chen (The Trade Desk)

  • Spring 2023: Yongchi Zhu (Baidu), Guanzi Chen (Ph.D. at Australian National University), Wanda Li (ByteDance), Nan Shen, Zirun Li

  • Spring 2022 Jingge Wang (Ph.D at TBSI), Yicong Li (Ph.D at Harvard)