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Department of Computing

The Hong Kong Polytechnic University

PQ741, Mong Man Wai Building

Hung Hom, Kowloon, Hong Kong

Wanyu is a research assistant professor in the Department of Computing at The Hong Kong Polytechnic University.

Wanyu’s main research interest is in developing machine learning algorithms for graph-structured data. Currently, her research activities focus on model explanations for graph neural networks and trustworthy machine learning. Wanyu’s methods of graph representation learning have been applied to various fields, such as computer vision and social networks.

Wanyu enjoys reading, singing, and jogging in her leisure time. She also loves to visit new places, meet new friends, and explore nature.

We are looking for motivated Post-doctoral Fellows, Research Assistants, and Ph.D. Students who are interested and experienced in responsible machine learning (interpretability, privacy, fairness, robustness, etc.) and general graph machine learning. 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.

Research Intern

  • Zehui Lin (Undergraduate student at the University of Sydney), 11/2022-

  • Mingxuan Ouyang (Master student at The Hong Kong Polytechnic University), 07/2022-

  • Ziyi Zhang (Master student at South China University of Technology), 05/2022-

news

Sep 21, 2022 Our paper, Rigging GNN-Based Social Status by Adversarial Attacks in Signed Social Networks, was accepted by TIFS 2022. :smile:
Sep 11, 2022 Our paper on GNN privacy, Solitude, was accepted by TIFS 2022. :smile:
Sep 11, 2022 One paper was accepted by TNSE 2022 and one was accepted by TKDD 2022. :sparkles:
Jun 22, 2022 Our paper, OrphicX, received the best paper finalist at CVPR 2022.
May 17, 2022 Serving as an Associate Editor for  IEEE Transactions On Neural Networks and Learning Systems (TNNLS).
May 12, 2022 Invited talk on GNN Interpretability at  Usslab,  Zhejiang University.
Mar 29, 2022 Our paper on GNN Interpretability, OrphicX, was selected as an oral presentation in CVPR 2022. :sparkles:
Mar 25, 2022 Invited talk on GNN Interpretability at  University of Glasgow and  International Centre for Mathematical Sciences.