Wanyu is an Assistant Professor in the Department of Computing at The Hong Kong Polytechnic University. Wanyu is serving as an Associate Editor for  IEEE Transactions On Neural Networks and Learning Systems (TNNLS) and Associate Editor for  IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI).

Wanyu’s primary research interest is in 1) AI for science. We focus on developing machine learning (ML) techniques (GNNs, diffusion, etc.) to accelerate scientific simulations and design (applications in materials, structure safety); 2) creating caollaborative AI systems (federated learning/multi-agent systems) with various trustworthy objectives, such as interpretability, privacy and safety.

Research Team

• Mingxuan Ouyang (Ph.D. Candidate, Previously Master Student at HK PolyU)
• Haowei Hua (Ph.D. Candidate, Previously Master Student at the University of Electronic Science and Technology of China (UESTC))
• Jiangwen Dong (Ph.D. Candidate, Previously Undergraduate Student at Zhejiang University)
• Zhuoran Li (Ph.D. Candidate, Previously Master Student at HK PolyU and Undergraduate at University of Washington-Seattle)
• Guodong Du (incoming Ph.D. Candidate, Previously Undergraduate Student at University of Electronic Science and Technology of China (UESTC))
• Zeyu An (incoming Ph.D. Candidate, Previously Master Student at the University of Electronic Science and Technology of China (UESTC))
• Zehui Lin (Research Assistant, Previously Undergraduate Student at the University of Sydney)
• Minfeng Wu (Research Assistant, Previously Undergraduate Student at Xiamen University)
• Xu Sun (Research Assistant, Undergraduate Student at HK PolyU)
• Jingwen Yang (URIS Program, Undergraduate Student at HK PolyU)
• Shuxiu Jia (URIS Program, Undergraduate Student at HK PolyU)



Alumni

• Jian Chen, an Assistant Professor at China University of Geosciences (Wuhan)
• Zhengzhong Wang, an Assistant Professor at Xiamen University



We are looking for motivated Post-Doctoral Fellows and Ph.D. Students who are interested and experienced in AI for Science and trustworthy AI. Send me your CV (GPA, publications, etc.) and your transcript via email if you are interested in working with me at PolyU. Candidates who have strong mathematics backgrounds and programming skills are preferred.