AI-Enabled Research Automation by Professor Yue Zhang

With the development of AI technologies, the pace of research in the field of artificial intelligence has been continuously accelerating. AI-enabled scientific research has made significant progress. AI scientists are a new field that has emerged over the past two years. Its most notable characteristic is that artificial intelligence leads the entire scientific research workflow. The development of AI scientists has the potential to help humans significantly improve the efficiency of technological R&D, while also exerting a profound impact on the paradigm of research publication. In this talk, I will share some research on AI scientists, including end-to-end execution of the full research workflow and a general-purpose disciplinary data collection system. In addition, I will share how AI can help the research community adapt to a faster pace of research and promote new paradigms for academic exchange and publication.

Professor at Westlake University, Vice Dean of the School of Engineering, ACL Fellow. He received a B.S. degree in Computer Science from Tsinghua University in 2003, and a Ph.D. degree in Computer Science from the University of Oxford in 2009. From 2010 to 2012, he conducted postdoctoral research at the University of Cambridge. His main research areas include natural language processing, language models, and trustworthy artificial intelligence. He authored the Cambridge University Press book Natural Language Processing - A Machine Learning Perspective, and wrote the natural language processing entry for the Oxford Bibliography. He served as Program Committee Chair for CCL 2020, EMNLP 2022, and LMG 2025; General Chair for NLPCC 2026 and AACL 2026; as Editor-in-Chief of LLM Journal; Action Editor of TACL; and Associate Editor of IEEE/ACM TASLP, IEEE TBD, and ACM TALLIP.