 | Prof. Jiyou JiaPeking University, China Dr. Jiyou Jia is a full professor and the Head of the Department of Educational Technology, Graduate School of Education, Peking University, China and is also the founding director of International Research Center for Education and Information at Peking University. He serves concurrently as the Vice Principal of Science at Xinxin School affiliated to Peking University High School. He is the responsible professor for the national-level online and offline blended first-class undergraduate course "Education and Artificial Intelligence". He was invited to work as a guest professor by School of Education, Technical University of Munich, Germany, a Distinguished Professor at Institute for Research in Open and Innovative Education, the Open University of Hong Kong China, and a visiting professor by the Education University of Hong Kong China. His research interests include educational technology and artificial intelligence in education, especially in TELL (Technology Enhanced Language Learning), math education with ICT, and decision making support system. He has been responsible for a dozen of national projects and international cooperation projects. His has won a number of national and international prizes, and published more than 150 articles in internationally or nationally peer-reviewed journals and conferences. Title: The Development and Application of a Math Intelligent Assessment and Tutoring System (MIATS V2.0) in Math Education Based on Big-data Mining Abstract:This speech introduces an intelligent mathematical assessment and tutoring system MIATS V2.0, which can not only provide adaptive assessment for students based on big data mining, but also guide students individually to solve difficult questions step by step. Four quasi-experiments in schools were conducted to evaluate the effect of this system on students’ performance. The analysis of the collected data demonstrates that the system can provide personalized assessment and tutoring and enhance the students’ learning performance, and is an effective approach to realize the value-added evaluation, the integration of testing and learning, and the promotion of learning through testing. This study provides a valuable reference for utilizing intelligent assessment and tutoring systems to help implement the macro policies such as student assessment reform, reducing the students’ burden and increasing the educational efficiency. |
 | Prof. Xiaoyan KuiCentral South University, China Xiaoyan Kui, PhD, professor, Central South University. Her main research interests include computer vision, medical image processing, and artificial intelligence. Xiaoyan Kui received her Ph.D. degree in Computer Science from Central South University, China, in 2012. She is currently a professor with the Department of Computer Science and Technology at Central South University. Her research interests include computer vision, medical image processing, and artificial intelligence. Title: Reform and Practice of Higher Education Empowered by AI Abstract: Based on the core needs of higher education reform, the report puts forward the core proposition of "building a personalized and intelligent education ecosystem with AI technology at its core", focusing on practical exploration in aspects such as teaching model innovation, scientific research capability assistance, and management efficiency upgrading. Taking the practical exploration of digital and intelligent transformation in Central South University as an example, it expounds the practical path of AI empowering higher education reform, and points out the key points for the future construction of digital and intelligent transformation. With the continuous iteration of AI technology and its deep integration with educational scenarios, artificial intelligence will become the core driving force supporting the digital transformation of higher education and cultivating innovative and compound talents, injecting new impetus into the long-term development of my country's higher education cause. |
 | Prof. Yan ZhangHuazhong University of Science and Technology, China PhD, Professor and Doctoral Supervisor at Huazhong University of Science and Technology (HUST), National Second-Class Psychological Counselor. She completed her visiting scholar fellowship at Yale University, USA from 2023 to 2025. Her research focuses on mental health, educational cognition and cognitive neuroscience. To date, she has published 158 peer-reviewed academic papers in domestic and international journals, including Journal of Affective Disorders, International Journal of Disaster Risk Reduction, Journal of Medical Virology, Psychophysiology, Children and Youth Services Review, Thinking Skills and Creativity, Acta Psychologica Sinica, and Development and Education of Psychology. Among these publications, 3 are Highly Cited Papers. Her single most cited paper has received 402 citations. According to Google Scholar, her total citation count reaches 1,843, with an h-index of 24 and an i10-index of 42. She has presided over 2 National Social Science Fund Projects, 1 Youth Program of the National Natural Science Foundation of China, 2 Humanities and Social Science Research Projects of the Ministry of Education, as well as more than 30 research projects at provincial, municipal and university levels. She has authored 8 monographs and participated in compiling 4 textbooks and reference books. She has been awarded 7 prizes for social science research and teaching achievements issued by the Sichuan Provincial People’s Government, Department of Education of Sichuan Province, Hubei Provincial Department of Education, Hubei Provincial People’s Government, Wuhan Municipal People’s Government and other authorities. Under her supervision, postgraduate students have won the First Prize of the "Top-Down Task Force" Special Competition in the National "Challenge Cup" Extracurricular Academic Science and Technology Competition for College Students, and the Second Prize of the National Tian Jiabing Teaching Skills Competition for Full-Time Master of Education Students (Science and Technology Education Major). Four of her policy consultation reports have been adopted by the internal reference of People’s Daily, Guangming Daily, the Hubei Provincial People’s Government and the CPC Hubei Provincial Committee. She serves as an ad-hoc reviewer for multiple SCI-indexed international journals, including International Journal of Psychology, Body Image and Psychological Reports. Her academic society appointments include: • Chairperson of the Basic Psychology Committee of Hubei Province • Director of the 13th Wuhan Psychological Society & Deputy Director of the Brain Imaging Committee • President of Hubei Marriage and Family Research Association Title: Neural Biomarkers of Anxiety and Depression Based on fNIRS and Machine Learning in Large-Scale Cohorts Abstract: Anxious depression carries higher disability and suicide risks, while subjective clinical scales fail to achieve accurate subtyping. Based on large cohorts, this study adopted 53-channel fNIRS combined with Verbal Fluency Task (VFT) and Autobiographical Memory Test (AMT), and leveraged machine learning to identify neural biomarkers of anxious depression. Distinct prefrontal hemodynamic patterns were observed among anxious depression, non-anxious depression and healthy controls. CNN and XGBoost models with SHAP interpretability reached an AUC of 0.93 for subtype discrimination, pinpointing the right prefrontal cortex and frontopolar area as core differential regions. This study identifies prefrontal hemodynamic dysfunction as a characteristic neural phenotype of anxious depression, establishes a non-invasive fNIRS-AI diagnostic pipeline, and provides neurobiological evidence for objective subtyping and early screening of depression. |
 | Prof. Jing GaoYantai Institute of Science and Technology, China Jing Gao is the Vice President of Yantai Institute of Science and Technology (YIST), an applied-science undergraduate university in Shandong Province, China. Under her leadership, YIST launched the "AI+ Ten-Intelligence Leap" strategic action plan in 2026, a comprehensive three-year roadmap to transform the university into an AI-native educational ecosystem. The plan covers ten dimensions: Smart Teaching, Smart Industry, Smart Research, Smart Global Link, Smart Care, Smart Governance, Smart Training, Smart Innovation, Smart Spirit, and Smart Teachers. Her research and administrative interests focus on the philosophy of higher education in the AI era, the transformation of applied undergraduate institutions, and the integration of industry and academia through intelligent systems. Title: Cold Tools and Warm Education: Building an AI-Based University Ecosystem Abstract: As generative AI reshapes every corner of higher education, a fundamental question emerges: when machines can explain concepts better, grade faster, and answer questions infinitely, what remains uniquely human in a university? This keynote draws on the speaker's book Cold Tools and Warm Education and the "AI+ Ten-Intelligence Leap" action plan implemented at Yantai Institute of Science and Technology to propose a new paradigm: the AI-Based University (ABU). Rather than treating AI as a bolted-on teaching aid, ABU reimagines the university as an AI-native ecosystem—like a forest where intelligence operates as sunlight, air, and rain. The presentation covers three pillars: (1) the philosophical tension between 'cold' AI efficiency and 'warm' human education; (2) the ten-intelligence strategic roadmap spanning smart teaching, industry-research fusion, student care, and governance; and (3) the four non-negotiables that universities must guard—human connection, critical thinking, value alignment, and the cultivation of complete persons. The speech concludes with an invitation to global collaboration in building universities that are not smarter factories, but thriving forests of human growth. |