👨‍🏫 About Me

I am currently a Professor and Associate Head of the Department of Computer Science and Technology at Guangdong University of Technology (GDUT). I received my B.Eng. degree from South China University of Technology (SCUT) in 2013, followed by M.Sc. and Ph.D. degrees from Hong Kong Baptist University (HKBU) in 2014 and 2019, respectively, supervised by Yiu-ming Cheung (张晓明) (IEEE/AAAS/IAPR Fellow, Changjiang Chair Professor, Chair Professor in Artificial Intelligence@HKBU). Following a postdoctoral fellowship at HKBU in 2019, I joined GDUT in 2020, where I was promoted to Associate Professor in 2022 and Professor in 2026.

My research focuses on Machine Learning (ML) and Data Science. Specifically, I collaborate closely with Yang Lu (卢杨), Mengke Li (李梦柯), and Yuzhu Ji (姬玉柱) on research topics including: ML on Heterogeneous Data, Unsupervised Federated Learning, Non-stationary Data Analysis. My research interests also inclue Large Language Models (LLMs) and AI for Science (AI4S). I have published over 90 papers in top-tier journals and conferences, including those in TPAMI, TNNLS, TIP, TMM, TCYB, SIGMOD, SIGKDD, NeurIPS, CVPR, ICCV, AAAI, IJCAI, and ACM MM.

Currently, I serve as an Associate Editor for the IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI). My academic and teaching contributions have been recognized with the Second Prize of the Guangdong Provincial Science and Technology Progress Award (2023), several Best Paper Awards (ISMIS’18, DOCS’24, 2020 IEEE CIS), and the MOE-Huawei “Intelligent Base” Pioneer Teacher Award.

🎉🎉Our Open-environment Machine learning Group (OMG) is constantly looking for self-motivated postgraduate and undergraduate students interested in scientific research. (For more details, please refer to About OMG).

🔥 News

• 2026/02:  🎉🎉 Two papers accepted to CVPR 2026, congratulations to Hezhao Liu and Shihao Hou!
• 2026/01:  🎉 One paper accepted as a long paper to DASFAA 2026, congratulations to Junyang Chen!
• 2026/01:  🎉 Two papers accepted to ICASSP 2026, congratulations to Shujie Qiu and Taixi Chen!
• 2026/01:  🎉🎉 The paper “Learning Self-Growth Maps for…” (TNNLS, 2025) has been selected as a Highly Cited Paper by the ESI.
• 2025/12:  🎉 Two papers accepted by IoTJ.

📝 Publications

ML on Heterogeneous Data

• Heterogeneous Feature Data Cluster Analysis
  SIGMOD’26 AAAI’26 ICDCS’24 AAAI’20

• Heterogeneous Feature Data Representation Learning
  SIGKDD’24 TNNLS’23 TPAMI’22 IJCAI’22

Unsupervised Federated Learning

• Federated Cluster Analysis
  IoTJ’26 AAAI’25 INS’25 DOCS’24

• Heterogeneous Federated Learning
  CVPR’26 CVPR’25 ECAI’25 TNNLS’25

Non-stationary Data Analysis

• Time-series Data Analysis and Applications
  AAAI’26 BIBM’25 PRICAI’25 ECAI’23

• Streaming Data & Concept Drift Analysis
  TETCI’26 AAAI’25 TNNLS’25 TCYB’25

List of Representative Publications

• SIGMOD’26 Categorical Data Clustering via Value Order Estimated Distance Metric Learning
  Yiqun Zhang, Mingjie Zhao, Hong Jia, Mengke Li, Yang Lu and Yiu-ming Cheung^✉

• CVPR’26 SECOS: Semantic Capture for Rigorous Classification in Open-World Semi-Supervised Learning
  Hezhao Liu, Jiacheng Yang, Junlong Gao, Mengke Li, Yiqun Zhang, Shreyank Gowda and Yang Lu^✉

• AAAI’26 Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering
  Zexi Tan, Xiaopeng Luo, Yunlin Liu and Yiqun Zhang^✉

• SIGKDD’24 QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering
  Junyang Chen, Yuzhu Ji, Rong Zou, Yiqun Zhang^✉ and Yiu-ming Cheung

• NeurIPS’24 Improving Visual Prompt Tuning by Gaussian Neighborhood Minimization for Long-Tailed Visual Recognition
  Mengke Li, Ye Liu, Yang Lu, Yiqun Zhang, Yiu-ming Cheung and Hui Huang^✉

• TMM’26 NIDC: General Task Backbone for Neuroimaging Analysis via Interpretable Deep Clustering
  Jiayu Ye, An Zeng^✉, Dan Pan, Junhao Chen, Jingliang Zhao, Yiqun Zhang and Yang Liu

• TAI’25 Trending Applications of Large Language Models: A User Perspective Survey
  Yiqun Zhang, Mingjie Zhao, Yunfan Zhang and Yiu-ming Cheung^✉

• TCYB’25 Online Heterogeneous Feature Selection
  Yiqun Zhang, Xinxi Chen, Lang Zhao, Yuzhu Ji, Peng Liu and Yiu-ming Cheung^✉

• TNNLS’25 Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering
  Yiqun Zhang, Sen Feng, Pengkai Wang, Zexi Tan, Xiaopeng Luo, Yuzhu Ji, Rong Zou and Yiu-ming Cheung^✉

• TPAMI’22 Learnable Weighting of Intra-attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes
  Yiqun Zhang and Yiu-ming Cheung^✉

  … … For a full list of publications, please visit DBLP | Google Scholar … …

🏆 Honors & Awards

• 2026/01: Outstanding Postgraduate Supervisor, Guangdong University of Technology
• 2025/12: Outstanding Editorial Board Member, Journal of Guangdong University of Technology
• 2024/12: Excellent Reviewer, ACM SIGKDD 2025
• 2024/08: Second Prize of Guangdong Provincial Science and Technology Progress Award (2023)
• 2024/08: Best Paper Award, The 6th IEEE International Conference on Data-driven Optimization of Complex Systems (DOCS 2024)
• 2022/09: MOE-Huawei “Intelligent Base” Pioneer Teacher Award
• 2021/06: First Prize, Young Teachers’ Teaching Competition, School of Computer Science, Guangdong University of Technology
• 2019/12: Research Performance Award, Department of Computer Science, Hong Kong Baptist University
• 2019/08: Champion, Postgraduate Research Paper Competition, IEEE Computational Intelligence Society (CIS) Hong Kong Chapter
• 2018/10: Best Student Paper Award, The 24th International Symposium on Methodologies for Intelligent Systems (ISMIS 2018), Springer
• 2014/06: Merit Scholarship, Department of Computer Science, Hong Kong Baptist University
• 2014/01: Merit Scholarship, Department of Computer Science, Hong Kong Baptist University

👨‍🎓 Educations

• 2014/09 - 2019/11: Ph.D. in Computer Science, Hong Kong Baptist University
  (Supervisor: Yiu-ming Cheung (Chair Professor, IEEE Fellow, AAAS Fellow, and IAPR Fellow)
• 2013/09 - 2014/11: M.Sc. in Computer Science, Hong Kong Baptist University
• 2009/09 - 2013/07: B.Eng. in Biomedical Engineering, South China University of Technology
• 2006/09 - 2009/07: Science Class, Shenzhen Hongling High School

💬 Invited Talks

• 2025/12: Clustering Analysis of Complex Distributed Data under Dynamic Environments, Shanxi University (SXU)
• 2024/12: Clustering Complex Data Under Dynamic Environments, Northeastern University (NEU) / State Key Laboratory of Synthetical Automation for Process Industries
• 2024/12: Clustering Analysis of Complex Data under Dynamic Environments, Guangdong University of Technology (GDUT)
• 2023/11: Learning from Complex Data with Cross-Coupled Heterogeneous Attributes, Southern University of Science and Technology (SUSTech)
• 2021/04: Insights into AI Research: A Dual Perspective from Authors and Reviewers, Guangdong University of Technology (GDUT)