Xiaojun Wu

1. Personal & Academic Information



Xiaojun Wu is a leading expert in pattern recognition and artificial intelligence, widely published with 400+ academic papers and 5 books. He has been recognized internationally for his work and holds multiple fellowships in professional societies. 



2. Education


  • B.Sc. in Mathematics, Nanjing Normal University, China (1991). 

  • M.S. in Pattern Recognition and Intelligent Systems, Nanjing University of Science and Technology, China (1996). 

  • Ph.D. in Pattern Recognition and Intelligent Systems, Nanjing University of Science and Technology, China (2002). 




3. Professional Positions


  • Distinguished Professor & Dean, Graduate School, School of AI & CS, Jiangnan University (current). 

  • Director, Sino-UK Joint Laboratory on AI. 

  • Director, Jiangsu Provincial Engineering Laboratory of Pattern Recognition & Computational Intelligence. 

  • Former faculty member at School of Electronics & Information, Jiangsu University of Science and Technology before joining Jiangnan University (2006). 




4. Research Interests



Professor Wu’s research focuses on:

  • Pattern Recognition Theory & Technology 

  • Computational Intelligence & Machine Learning 

  • Computer Vision 

  • Information Fusion 




5. Honors & Leadership


  • IAPR Fellow (International Association for Pattern Recognition), 2022 — one of ~21 worldwide selected in his class. 

  • Fellow, Asia-Pacific AI Association (AAIA) and Artificial Intelligence Industry Alliance (AIIA). 

  • NAAI Corresponding Member. 

  • National and Provincial Distinctions: New Century Excellent Talents (Ministry of Education, China), Jiangsu Province “333 Engineering” Leading Talent. 

  • Editorial roles in multiple international journals; committee member of IEEE Smart City Steering Committee and others. 




6. Scholarly Output


  • 400+ research papers in top journals and conferences (e.g., TPAMI, IJCV, TIP, CVPR, ICCV, NIPS). 

  • 5 books, including at least one English monograph (CRC Press). 

  • Google Scholar citations exceed 20,000+.