PhD, Information Technology
2023-07-01
2026-09-09
University of Technology Sydney
M.Eng, Electronic Information
2020-09-01
2023-06-30
Zhejiang Gongshang University
B.Eng, Electronic Information Engineering
2016-09-01
2020-06-30
Zhejiang Gongshang University
SARL: A Scalable Attribute-Informed Representation Learning Framework for Bipartite Graphs has been accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE). The work studies attribute-informed representation learning on bipartite graphs and scales it to large graphs.
MGDN: A Graph of Graphs Neural Network for Malware Detection is published in IEEE Transactions on Knowledge and Data Engineering (TKDE).
RIDA: a robust attack framework on incomplete graphs is published in World Wide Web Journal.
Neural Similarity Search on Supergraph Containment (Extended Abstract) appears in the proceedings of IEEE ICDE 2024.
I build machine learning algorithms for graph-structured data and database systems.
My work spans two directions: (1) graph neural network architectures that model complex, heterogeneous or incomplete graphs — fraud detection on e-commerce platforms, graph similarity computation, supergraph containment search and malware detection; and (2) learning-based methods for data management — using graph learning and representation techniques to speed up the algorithms behind databases and data-mining systems.
Recent work has appeared in KDD 2023 and IEEE TKDE (2024, 2025, 2026).
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