Professor Shugong Xu （徐树公）is a full professor in the Department of Intelligent Science at XJTLU’s School of Advanced Technology. He is an expert in artificial intelligence, pattern recognition, and wireless communication systems. 

After receiving his bachelor's drgree in Electronics at Wuhan University, Prof. Xu obtained his master degree in Pattern Recognition and Intelligent Control and his PhD in Communication and Information Systems at Huazhong University of Science and Technology (HUST). 

Professor Xu has a distinguished R&D and academic career of more than 30 years. Half of his career time spans in top industrial research labs, including Sharp Labs of America, Huawei 2012 Labs and Intel Labs. Prof. Xu has led many national and international projects and is a recipient of numerous honours, including the National Innovation Leadership Talent Award (2013) and the First Prize in Shanghai’s Natural Science Award (2023). He was named an IEEE Fellow in 2016 and won the Award for Advances in Communication from the IEEE Communication Society in 2017. Before joining XJTLU, Prof. Xu was a full professor at Shanghai University since 2016. His research output includes over 80 patents issued in US/WO/CN, and more than 200 peer-reviewed research papers. 

In AI and pattern recognition, he successfully developed next-generation license plate detection and recognition systems for unconstrained scenarios, lightweight and robust driver monitoring systems with mask resilience, and the world’s first large language model for organoids. In wireless communication systems, Professor Xu was the first to identify the limitations of the 802.11 MAC protocol in wireless ad hoc networks and elucidated the underlying reasons, catalysing research and standardisation processes for the IEEE 802.11s international standard. His research work also resulted in core patents that were incorporated into the 3GPP 4G standard. He has been promoting inter-disciplinary research in AI+wireless since 2017, with his team won top three in national-wide competitions in the past five years in a row. Professor Xu acted as pioneer in proposing the new research direction on channel foundation model (CFM), which will likely become one of the critical options in 6G Native AI. 

Professor Xu's recent research interests include foundation models ( CFM for 6G / wireless communication and sensing, protein foundation model for biomedicine, time series foundation model, etc),  multimodal sensing (especially for low altitude sensing and autonomous driving), AI for drug development (for example linker design for ADC and antibody design), as well as AI for wireless,.  

Professor Xu is looking for candidates for postdoc fellows, PhD/MS students, research assistants, undergraduate interns. Those who are interested in these positions are welcomed to enquire through email.

徐教授课题组招收博士后研究员、博士/硕士研究生、科研助理、本科生。欢迎感兴趣的同学通过电子邮件交流。

NEW! 2026.1  ♠♠♠    Two papers from Prof. Xu group accepted by ICASSP 2026：

“Dual Data Scaling for Robust Two-Stage User-Defined Keyword Spotting”；

“ ReinPATH： A Multimodal Reinforcement Learning Approach for Pathology”. 

NEW! 2025.12 ♠♠♠    Three survey papers from Prof. Xu group accepted  by IEEE Communications Surveys & Tutorials: and IEEE Comm Magazine:

“AI-driven Wireless Positioning: Fundamentals, Standards, State-of-the-art, and Challenges” 

"AI-Driven Channel State Information (CSI) Extrapolation for 6G: Current Situations, Challenges and Future Research"

"Sidelink Positioning: Standardization Advancements, Challenges and Opportunities"