The rapid advancement of Large Language Models (LLMs) and foundation models has brought unprecedented opportunities to various specialized domains. The healthcare and industrial sectors, in particular, stand at the forefront of this artificial intelligence revolution. In healthcare, large models are being increasingly applied to electronic health record (EHR) analysis, medical image diagnostics, drug discovery, and intelligent patient interactions, significantly enhancing diagnostic accuracy and operational efficiency. Similarly, in the industrial domain, these models are transforming smart manufacturing, predictive maintenance, supply chain optimization, and industrial robotics, driving the transition towards Industry 4.0. However, deploying large models in these high-stakes and knowledge-intensive domains presents critical challenges, including data privacy, domain adaptation, reliability, interpretability, and the mitigation of "hallucinations." This special session aims to bring together researchers, practitioners, and industry experts to discuss the latest advancements, methodologies, and practical applications of large models in medical and industrial fields.
Organizer: Assoc. Prof. Bowen Xing, University of Science and Technology Beijing, China
Dr. Bowen Xing is an Associate Professor and Master's Supervisor at the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). He received his B.S. and M.S. degrees in Computer Science and Technology from the Beijing Institute of Technology in 2017 and 2020, respectively. In February 2024, he obtained his Ph.D. from the Australian Artificial Intelligence Institute (AAII) at the University of Technology Sydney, under the supervision of Prof. Ivor W. Tsang. He joined USTB in March 2024. Dr. Xing's research focuses on the frontiers of Artificial Intelligence and Natural Language Processing, with a particular emphasis on LLM-based heterogeneous language information processing and its applications in vertical domains and knowledge-based systems. He has authored or co-authored over 20 high-impact papers as the first or corresponding author in top-tier AI and NLP journals and conferences, including IEEE TPAMI, ACL, and EMNLP. Furthermore, he actively serves the academic community as an Area Chair and Program Committee Member for prestigious conferences such as ACL, ICML, ACM MM, and AAAI.
Co-organizer: Senior Assoc. Prof. Rui Yang, Xi'an Jiaotong-Liverpool University, China
Rui Yang received his Ph.D. degree and B.Eng degree from National University of Singapore (NUS). His research interests are in Industrial AI and Brain-Computer Interface (BCI).
Dr. Yang is named a Highly Ranked Scholar (top 0.05%) in Transfer Learning by ScholarGPS, ranking 8th globally over the past five years, and is the Director of Centre for Intelligent Control and Optimization (XJTLU-AUO Collaborative Research Centre). Dr. Yang serves as Associate Editor for esteemed international SCI/ESCI indexed journals, including IEEE Transactions on Instrumentation and Measurement (IF=7.0), Neurocomputing (IF=6.7), Cognitive Computation (IF=7.4) and International Journal of Network Dynamics and Intelligence (IF=15.3).
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