报告人：张俊华 博士 新南威尔士大学
主持人：金嘉晖
报告时间：2025年1月2日（周四）上午10:00
报告地点：东南大学九龙湖校区计算机楼513报告厅
报告摘要：Graphs are fundamental data structures for modeling complex relationships in various domains. Efficient graph queries, such as path queries, reachability queries, and kNN queries, are essential problems in graph data processing and analysis. However, graph queries are computationally expensive due to the large size of graphs and the complexity of queries. In this talk, I will present our recent advancements in accelerating graph queries with graph indexing techniques. We propose a series of graph indexing techniques to accelerate graph queries, including path queries, reachability queries, and kNN queries. These techniques have demonstrated significant performance improvements over state-of-the-art methods in terms of query processing time and index construction time. These works have been published in top-tier conferences and journals, such as VLDB, VLDBJ, and ICDE.
报告人简介：Dr. Junhua Zhang (张俊华) has been working as a postdoctoral researcher at the University of New South Wales (UNSW) since 2022, advised by Prof. Wenjie Zhang. He received his Ph.D. degree in AAII from the University of Technology Sydney (UTS) in 2023, under the supervision of Prof. Lu Qin. He got his M.S. degree and B.S. degree from the Shandong University in 2019 and 2016, respectively. His research interests include graph data processing, distributed graph processing systems, and cloud computing. He has published several papers in top-tier conferences and journals. He has served as a (external) reviewer for several top-tier conferences and journals, such Sigmod 2023, ICDE 2024, Dasfaa 2020-2025, etc.
