Journal of Big Data Research

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Assoc. Prof. Jinpeng Chen, Beijing University of Posts and Telecommunications, expert in machine learning, recommendation systems, social network analysis, and continual learning.

China

Associate Professor, School of Computer Science (National Pilot Software Engineering School),

Beijing University of Posts and Telecommunications (BUPT), China 

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Jinpeng Chen

Address:

10 Xitucheng Rd, Haidian Dist,

Beijing, 100876, P.R.China.

Research Interests:

  • Machine Learning
  • Recommendation Systems
  • Social Network Analysis
  • Data Mining & Knowledge Discovery
  • Clustering, Classification, Prototype / Continual Learning
  • Information Extraction, Data Science

Biography:

Jinpeng Chen is an Associate Professor of Computer Science at Beijing University of Posts and Telecommunications (BUPT), where he leads and participates in research in machine learning, data mining, recommendation systems, social network analysis, and related areas. He obtained his PhD from Beihang University in 2016, under advisor Deyi Li. Before that, he completed undergraduate studies in Electronic Information Science and Technology at BUPT. Over his career, he’s held positions as Assistant Professor, then Associate Professor at BUPT. His contributions include developing graph neural network methods, prototype replay methods, continual learning techniques, and improving recommender and classification systems. He has published many SCI/EI papers, serves on editorial and review committees, and mentors graduate students.​


Achievements (Awards & Honors): 

  • ICONIP Best Paper Award (2022); Zhou Jiongpan Outstanding Young Teacher Inspirational Award; Beijing Mobile Teaching Innovation Award; Best Researcher Award (2025); 8 patents


Current Research Projects:

  • Adaptive graph diffusion networks; multimodal continual learning; prototype replay in semantic segmentation; AI-driven recommender systems


Academic Profiles of Jinpeng Chen:

Explore his academic and professional presence across trusted platforms:

Publications:

Recent publications show work in segmentation, continual learning, prompts, and class-incremental methods.

  • Jinpeng Chen, Runmin Cong, Yuzhi Zhao, Horace Ho Shing Ip, and Sam Kwong — “SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning,” ICML, 2025.
  • Jinpeng Chen, Runmin Cong, Yuxuan Luo, Horace Ho Shing Ip, and Sam Kwong — “Replay without saving: Prototype derivation and distribution rebalance for class-incremental semantic segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.
  • Yuxuan Luo, Jinpeng Chen, Runmin Cong, Horace Ho Shing Ip, and Sam Kwong — “Trace back and go ahead: Completing partial annotation for continual semantic segmentation,” Pattern Recognition, 2025.
  • Hang Xiong, Runmin Cong, Jinpeng Chen, Chen Zhang, Feng Li, Huihui Bai, and Sam Kwong — “MM-Prompt: Multi-modality and Multi-granularity Prompts for Few-Shot Segmentation,” ACM Multimedia, 2025.
  • C Sun, J Hu, H Gu, J Chen, W Liang, M Yang — “Scalable and adaptive graph neural networks with self-label-enhanced training,” Pattern Recognition, 2025

 

Last Updated on September  12, 2025