Research

Research Interests

• Causality and machine learning: invariant/stable learning, OOD generalization, etc.
• Applications of casual discovery and inference: debiasing in recommender systems and telecommunications, root cause analysis, etc.
• Kernel methods and hypothesis testing

Recent Talks

• Invited talk, “Introduction to causal discover”, OOD group, August 2022
• Invited talk, “Causality and machine learning: How they help each other?”, Institute of Computing Technology, Chinese Academy of Sciences, August 2022
• Invited panelist on “Causal inference and learning”, VALSE (Vision And Learning SEminar) webinar, August 2021.
• Invited talk on “Gradient based causal structure learning”, Institute of Natural Science, Shanghai Jiaotong University, May 2021.
• Invited talk on “Gradient based causal structure learning: methods and applications” at several internal departments of Huawei, 2020.
• Invited talk on “Causal discovery with reinforcement learning” at Leiphone.com and Tianjin University (online), March, 2020.
• Invited talk on “Gradient based causal structure learning” at International Workshop on Causal Modeling and Machine Learning (CaMal 2019), Guangzhou, December, 2019.
• Invited lectures on machine learning, including introduction, ensemble methods and feature engineering, at Huawei Wireless Department, Shanghai, March, 2019.