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Mingyuan is a Research Associate Professor (特聘副研究员) in the School of Computer Science at Peking University.

Mingyuan’s main research interest is in developing machine learning algorithms for graph-structured data. Currently, his research activities focus on model explanations for graph neural networks and AI for graph theory. Mingyuan’s methods of graph representation learning have been applied to various fields, such as bioinformatics and social networks.

Research Team

• Congzhou Chen (Associate Professor at Beijing University of Chemical Technology, Previously Ph.D. at Peking University)
• Ke Chen (Post-Doctoral Fellow, Previously Ph.D. at East China Normal University)
• Wei Chi (Ph.D. Candidate, Previously Master Student at Peking University)
• Zichao Zhang (Ph.D. Candidate, Previously Undergraduate Student at Lanzhou University)
• Weilin Hao (Ph.D. Candidate, Previously Undergraduate Student at Central South University)
• Chenghao Yang (Incoming Ph.D. Candidate, Previously Master Student at Peking University)
• Xiaolu Zhang (RA, Master Student at City University of Hong Kong)



We are looking for motivated Post-Doctoral Fellows and Ph.D. Students who are interested and experienced in responsible machine learning (interpretability,fairness, robustness, etc.), machine learning for graph-structured data. Send me your CV (GPA, publications, etc.) and your transcript via email if you are interested in working with me at PKU. Candidates who have strong mathematics backgrounds and programming skills are preferred.