Jingbang Chen

Research Assistant Professor

The Chinese University of Hong Kong，Shenzhen

Education Background

Educational Background：

  • 2023-2025: University of Waterloo, Computer Science, Doctoral Degree (Full-time)
  • 2020-2022: Georgia Institute of Technology, Computer Science, Master Degree (Full-time)
  • 2016-2020: Zhejiang University, Computer Science, Bachlor Degree (Honors) (Full-time)

 

Work Experience：

  • 2025-Present: School of Data Science, The Chinese University of Hong Kong, Shenzhen, Research Assistant Professor
Research Fields
Trustworthy AI, Graph Algorithm and Data Structure Design, Large-scale Data Management and Data Mining
Email
jingbangchen@slai.edu.cn
Biography

Dr. Jingbang Chen is a Research Assistant Professor at the Chinese University of Hong Kong, Shenzhen. He receives his Ph. D degree from University of Waterloo, his Master degree from Georgia Institute of Technology and his bachelor degree from Zhejiang University. His research revolves around the design, analysis, and implementation of provably efficient graph algorithms and data structures, with extensions on large-scale data management, data mining, machine learning and artificial intelligence. Til now, he has published several papers in the areas of database, data mining, theoretical computer science and machine learning, and many of them were published in top-tier conferences. He is highly involved with Competitive Programming activities. Previously, he participated in ICPC World Finals and has won ICPC regional champion titles along with twelve gold medals. He has served as the chief judge for several ICPC Asia regionals and the coach of training camps including North American Programming Camp. He is also the founder and co-president of the Universal Cup. Cooperation in trustworthy AI analysis, AI + Data Management, Data Mining and applications from outstanding students are welcome.

Academic Publications
  1. Jingbang Chen, Weinuo Li, Yingli Zhou, Hangrui Zhou, Qiuyang Mang, Can Wang, Yixiang Fang, Chenhao Ma, “Scalable Approximate Biclique Counting over Large Bipartite Graphs”, International Conference on Very Large Data Bases (VLDB 2026)
  2. Jingbang Chen, Xinyuan Cao, Alicia Stepin, Li Chen, “On the Power of Learning-Augmented Search Trees”, International Conference on Machine Learning (ICML 2025)
  3. Jingbang Chen, Qiuyang Mang, Hangrui Zhou, Richard Peng, Yu Gao, Chenhao Ma， “Scalable Algorithm for Finding Balanced Subgraphs with Tolerance in Signed Networks”， ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
  4. Qiuyang Mang, Jingbang Chen, Hangrui Zhou, Yu Gao, Yingli Zhou, Qingyu Shi, Richard Peng, Yixiang Fang, Chenhao Ma，”Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index”, International Conference on Very Large Data Bases (VLDB 2025)
  5. Jingbang Chen, Meng He, J. Ian Munro, Richard Peng, Kaiyu Wu, Daniel J. Zhang, “Distance Queries over Dynamic Interval Graphs”, International Symposium on Algorithms and Computation (ISAAC 2023) and Computational Geometry: Theory and Applications (Volume 122)
  6. Jingbang Chen, Li Chen, Yang P. Liu, Richard Peng, Arvind Ramaswami,. “Exponential Convergence of Sinkhorn Under Regularization Scheduling”,.SIAM Conference on Applied and Computational Discrete Algorithms (ACDA 2023)
  7. Jingbang Chen, Yu Gao, Yufan Huang, Richard Peng, Runze Wang, “Hardness of Graph-Structured Algebraic and Symbolic Problems”, Algorithms and Data Structures (WADS 2023)