AICCC 2026

Keynote Speakers

Keynote Speaker I

Prof. Runhe Huang,
Hosei University, Japan

Runhe Huang received her B.Sc. in Electronics Technology from the National University of Defense Technology, China, in 1982, and her Ph.D. in Computer Science and Mathematics from the University of the West of England, UK, in 1993. She has been a full professor in the Faculty of Computer and Information Sciences at Hosei University, Japan, since 2003. She served as Head of the Department of Computer Science from 2008 to 2010 and is currently Deputy Director of the Hosei University Library. She is a Senior Member of IEEE and ACM and served as Chair and Vice Chair of the IEEE CIS Smart World Technical Committee (SWTC) from 2019 to 2022. She was the General Chair of the 2024 IEEE Smart World Congress and the 2024 IEEE International Conference on Ubiquitous Intelligence and Computing (UIC). She is an Associate Editor of IEEE Transactions on Computational Social Systems and a member of the Editorial Board of IEEE Systems, Man, and Cybernetics Letters. She has also served as an Associate Editor of Frontiers in Neuroinformatics and the International Journal of Network Dynamics and Intelligence. Her research interests include artificial intelligence, ubiquitous intelligence and computing, machine intelligence, cognitive computing, knowledge modeling, and embodied intelligence for robotics. She has authored over 250 academic papers.

Keynote Speaker II

Prof. Gaurav Sharma (IEEE Fellow, SPIE fellow)
University of Rochester, USA

Gaurav Sharma is a professor in the Departments of Electrical and Computer Engineering, Computer Science, and Biostatistics and Computational Biology, and a Distinguished Researcher in Center of Excellence in Data Science (CoE) at the Goergen Institute for Data Science at the University of Rochester. He received the PhD degree in Electrical and Computer engineering from North Carolina State University, Raleigh in 1996. From 1993 through 2003, he was with the Xerox Innovation group in Webster, NY, most recently in the position of Principal Scientist and Project Leader. His research interests include data analytics, cyber physical systems, signal and image processing, computer vision, and media security; areas in which he has 56 patents and has authored over 225 journal and conference publications. He served as the Editor-in-Chief for the IEEE Transactions on Image Processing from 2018 through 2020, and for the Journal of Electronic Imaging from 2011 through 2015. He is a member of the IEEE Publications, Products, and Services Board (PSPB), the IEEE Signal Processing Society Board of Governors, and chaired the IEEE Conference Publications Committee in 2017-18. He is the editor of the Digital Color Imaging Handbook published by CRC press in 2003. Dr. Sharma is a fellow of the IEEE, a fellow of SPIE, a fellow of the Society for Imaging Science and Technology (IS&T) and has been elected to Sigma Xi, Phi Kappa Phi, and Pi Mu Epsilon. In recognition of his research contributions, he received an IEEE Region I technical innovation award in 2008 and the IS&T Bowman award in 2021. Dr. Sharma served as a 2020-2021 Distinguished Lecturer for the IEEE Signal Processing Society.

Keynote Speaker III

Prof. Cheng-Hsuan Li
National Taichung University of Education, Taiwan

Dr. Cheng-Hsuan Li is a Chair Professor at the Graduate Institute of Educational Information and Measurement and Director of the Center for Institutional Affairs at National Taichung University of Education, Taiwan. He served as Director-General of the Department of Information and Technology Education, Ministry of Education, Taiwan, from August 2022 to January 2024. He assisted in the planning and implementation of Taiwan’s Digital Learning Enhancement Plan for Grades 1–12 Students (2022–2025) and is currently the Principal Investigator of the Educational Big Data Project under Taiwan’s AI Talent Ark Project (2026–2029). In 2023, he led the development of TALPer, a generative AI Companion embedded in the Taiwan Adaptive Learning Platform (TALP) for nationwide K–12 use. Since its nationwide launch, TALPer and its AI Genies—such as self-directed learning, drawing, reading and thinking, and joyful learning genies—have supported over 750,000 teachers and students across Taiwan. His research focuses on artificial intelligence in education, statistical learning, educational measurement, learning analytics, adaptive learning systems, AI-supported assessment, and human-AI teaming. He advocates trustworthy and human-centered educational AI that supports personalized learning, teacher decision-making, self-regulated learning, and deeper student understanding.

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