 | Prof. Haofen WangTongji University, China Wang Haofen, recipient of the Shanghai Outstanding Doctoral Graduate Award, is a tenured professor and PhD supervisor at Tongji University. His research focuses on knowledge graphs and knowledge-enhanced large language models, as well as the practical application of AI in industry. His key achievements include KAG-Thinker—the world’s first knowledge-enhanced reasoning model—the memory operating system MemOS (with over 10,000 Star ratings) and the large language model evaluation platform AI-Ceping (with over 300,000 monthly active users), which have been deployed across various scenarios such as airport traffic control and financial risk management. He has published six monographs, including *Knowledge Graphs* and *Retrieval-Augmented Generation: Theory and Practice*, and has authored over 100 high-impact conference and journal papers, with over 13,000 citations on Google Scholar. He has led more than 10 national AI projects, including key and general projects under the National Natural Science Foundation of China and the National Major Special Project on Next-Generation AI. He has received honours such as the First Prize for Scientific and Technological Progress from the China Communications Association, the 2026 IF Design Award, the HCII Best Paper Award, and the DASFAA Best Student Paper Award. He previously served as CTO of two AI unicorn companies, where he created the world’s first interactive, trainable virtual idol, ‘Amber·Xuyan’; The intelligent customer service bots he has developed have cumulatively served users over 10 billion times. Currently, he holds the following positions: inaugural rotating chair of OpenKG, the world’s largest open knowledge graph community; deputy director of the Terminology Working Committee of the Chinese Computer Society; secretary-general of the Natural Language Processing Technical Committee; councillor of the Chinese Society for Chinese Information Processing; executive committee member of the Large Model Technical Committee; deputy secretary-general of the Language and Knowledge Computing Technical Committee; and deputy director of the Natural Language Processing Technical Committee of the Shanghai Computer Society. |
 | Prof. Yunwen ChenDataGrand Co., Ltd., China Chen Yunwen, Chairman of Daguan Data. He holds a PhD in Computer Science from Fudan University and is an expert under the national ‘Ten Thousand Talents Programme’, a recipient of the State Council’s Special Allowance, one of the first experts to be awarded the senior-most professional title in artificial intelligence, and a Distinguished Member of the Chinese Computer Society. He has applied for nearly a hundred national technical invention patents and has received honours including the ACM International Data Mining Competition championship and the Wu Wenjun Artificial Intelligence Award. |
 | Prof. Hai ZhaoShanghai Jiao Tong University, China Zhao Hai is a tenured professor and PhD supervisor at the School of Computer Science, Shanghai Jiao Tong University. He currently serves as Director of the General Artificial Intelligence Research Institute at the School of Computer Science, Shanghai Jiao Tong University. His research interests include foundational models of artificial intelligence, fundamental theories of general artificial intelligence, and brain-inspired intelligence. He has published over 200 papers, including more than 100 CCF-A and B category papers and over 20 SCI-indexed papers in the first tier of the Chinese Academy of Sciences (CAS) over the past five years, comprising five papers in the journal TPAMI. His Google Scholar citation count currently exceeds 15,000. He is a professional member of ACM, a committee member of the Chinese Information Processing Technical Committee of the Chinese Computer Society, and Deputy Director of the Artificial Intelligence Technical Committee of the Shanghai Computer Society. He serves as an executive editor for the ACL rolling review system and TACL, as well as a (senior) programme chair for AAAI, IJCAI and NeurIPS. In recent years, he has achieved top results on international natural language understanding benchmarks such as RACE, SQuAD 2.0, HotPot-QA and HellaSWag on multiple occasions, and has submitted understanding systems that were the first to surpass human performance. In 2023, Tsinghua University Press published *Natural Language Understanding*, the first Chinese monograph and textbook to cover large language models. He has led the development of the BatGPT series of large language models and deployed them in vertical applications with multiple industry partners, serving various national departments, including Shanghai’s first large-model application system procured by a government department. He proposed and released the Brain-Inspired Large Language Model (BriLLM), which received key funding under the ‘Jiaotong University 2030’ programme, pioneering a new path towards brain-inspired general artificial intelligence. He has been consecutively selected as an Elsevier Highly Cited Researcher from 2022 to 2025. |