The New Era of AI Agents
Prof. Wen-Huang Cheng (University Distinguished Chair Professor; Fellow, IEEE&IET)
National Taiwan University, Taiwan
ABSTRACT
In recent years, AI development has progressed from the traditional "software" era into the transformative era of "large-scale AI models." During the software era, AI systems primarily relied on hardcoded rules, limiting their ability to make nuanced judgments or adapt to dynamic situations—traits inherent to human cognition. In contrast, today’s large models can process unstructured inputs such as natural language and produce diverse outputs, including text, images, and more. This dynamic capability brings AI closer to human-like reasoning and sets the stage for the next evolutionary step: the era of AI Agents. AI Agents are no longer static programs governed by predefined rules. Instead, they leverage large models to continuously learn, self-improve, and flexibly adapt to evolving environments and contexts. This talk will offer an in-depth overview of the foundational technologies and application scenarios driving AI Agent development. It will also explore current trends and key challenges, providing actionable insights and inspiration for technology innovators.
SPEAKER BIOGRAPHY
Wen-Huang Cheng is a University Distinguished Chair Professor in the Department of Computer Science and Information Engineering at National Taiwan University and a Visiting Professor at the Korea Advanced Institute of Science and Technology (KAIST). His current research interests include multimedia, computer vision, and machine learning. He has actively participated in international events and played significant leadership roles in prestigious journals, conferences, and professional organizations. These roles include serving as Editor-in-Chief for IEEE CTSoc News on Consumer Technology, Senior Editor for IEEE Consumer Electronics Magazine (CEM), Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) and IEEE Transactions on Multimedia (TMM), General Chair for ACM MMAsia (2023), IEEE ICME (2022), and ACM ICMR (2021), Technical Program Chair for ACM MM (2025), ACM ICMR (2022), IEEE ICME (2020), IEEE VCIP (2018), Chair for IEEE CASS Multimedia Systems and Applications (MSA) technical committee, and governing board member for IAPR. He has received numerous research and service awards, including the NVIDIA Academic Grant Program Award (2025), the 2024 Best Paper Award of IEEE Consumer Electronics Magazine, the Best Paper Award at the 2021 IEEE ICME and the Outstanding Associate Editor Award of IEEE TMM (2021 and 2020, twice). He is an IEEE Fellow, IET Fellow, and ACM Distinguished Member.
International Collaborative Engineering Education
Prof. Hamadou Saliah-Hassane
TÉLUQ University, Canada
ABSTRACT
Our presentation will focus on the challenges, issues and opportunities facing virtual training organizations for engineers and technicians, thanks to information and communication technologies and enhanced technological learning tools. Based on the case of the IEEE Education Society’s Virtual Graduate Study Consortium (VGSC) initiative, we will show how we have succeeded in our venture to train and support students appropriately by taking them out of the classrooms and laboratories of their own educational institutions. We did this by adopting an approach based on participatory action research, and by implementing a Collaborative Engineering. The actors in our dynamic are students, industries and research professors from universities and educational institutions involved in the development of IEEE standards. Several IEEE Organizational Units are also involved.
SPEAKER BIOGRAPHY
Professor Saliah-Hassane earned a PhD in Electrical and Computer Engineering from McGill University in Montreal, a Bachelor and Master of Applied Science degree from École Polytechnique de Montréal, Canada. He retired in 2024 as a full Professor from TELUQ University in Montreal where he taught Informatics and Computer Networks and Security. He is now an Associate Professor in several universities including University Abdou Moumouni in Niger and an Affiliate Professor at Florida Atlantic University in US. His research interests are on Intelligent Distributed Systems and Mobile Robotics.
Professor Saliah-Hassane has taught at University of Niamey, Republic of Niger (1985-1987) and was Head of Electrical Engineering Department of The Engineering School of Mines, Industry and Geology (EMIG) of the former Economic Community of West Africa in Niamey, Niger (1989-1991).
Professor Saliah-Hassane is the current Vice President Educational Activities of IEEE Education Society (2022-2024). He chaired the Montreal IEEE Education Society Chapter (2005-2022). He was the Past Chair of IEEE Education Society Standards Committee (2010 - 2021) and the Past Chair of the Working Group of the joint standardization activity on “Secure and Trusted Learning Systems” (2019 -2021) sponsored by IEEE Education Society, IEEE Industrial Electronics Society (IES) and IEEE Computer Society Learning Technology Standards Committee (CS/LTSC).
Professor Saliah-Hassane has received many awards in recognition of his accomplishments, including the 2024 Latin America and Caribbean Consortium (LACCEI) Academic Merit Medal and the IEEE Education Society’s EdWin C. Jones, Jr. Meritorious Service Award (2019). He was also recognized with highest academic distinction of “Commander of the Order of Academic Palm” by Republic of Niger, his home country. And aligned with his work on Distributed Embedded Systems, the IEEE Standards Association award with appreciation for chairing and contributing to the development of IEEE Standard 1876™ - 2019 on “Networked Smart Learning Objects for Online Laboratories” (2019), the IEEE SA 2019 Emerging Technology Awarded to IEEE SA 1876™ - 2019 Working Group.
Designing Optimal Latent Space toward Knowledge Extrapolation
Prof. Kenji Yamanishi
Tokyo University, Japan
ABSTRACT
Recent success of AI/machine learning technologies is largely due to the embedding of the original data into a latent space, where we can extract essential features necessary for data mining tasks such as prediction, classification, and clustering. There are critical issues 1) how should we design an optimal latent space, depending on the nature of the data? and 2) how should we utilize the latent space not only for learning in a classical sense, but also for knowledge extrapolation? This talk introduces recent advanced technologies for addressing these issues. As for 1), I show a novel methodology for optimally selecting the kind of space (Euclidean or non-Euclidean), dimensionality, and curvature for the latent space. I show that they are obtained within a unifying framework of the minimum description length (MDL) principle. As for 2), I show that a novel but reliable knowledge can be generated by modeling the embedded data with Gaussian mixture model and then manipulating it adequately on the basis of the MDL principle. Both 1) and 2) are widely applicable to the areas including graph mining and generative AI.
SPEAKER BIOGRAPHY
Kenji Yamanishi is a professor in the Graduate School of Information and Technology at the University of Tokyo. He received the degree of doctor engineering from the University of Tokyo, 1992. He used to work for NEC Corporation from 1987 to 2008, and his final position was a fellow. He joined the University of Tokyo in 2009, and was an associate dean of the graduate school(2019-2021). His current research interests include information-theoretic machine learning, data mining, and computational ophthalmology. Specifically, he is a pioneer of learning theory based on the minimum description length (MDL) principle. He has also contributed to the area of anomaly/change detection and text mining with their applications to industries. He has been working as an area chair or a regular or senior program committee member of ACM SIGKDD(Knowledge Discovery and Data Mining) for years, an associate editor of KAIS(Knowledge and Information Systems) and IJDSA(International Journal of Data Science and Analytics), an editorial board member of Entropy, and a honorary chair of WITMSE (Workshop on Information Theoretic Methods for Science and Engineering). He is a fellow of IEICE(Institute of Electronics, Information and Communication Engieers) and a senior member of IEEE. He obtained several awards including IBM Faculty Awards, Fuji-Sankei Businetss Award, etc. He is an author of the book: “Learning with the Minimum Description Length Principle” published by Springer in 2023.
Why Should Intellectual Styles Matter in Information Technology and Education Technology?
Prof. Li-fang Zhang
The University of Hong Kong, Hong Kong
ABSTRACT
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SPEAKER BIOGRAPHY
Li-fang Zhang is a Professor of Psychology and Education in the Faculty of Education at The University of Hong Kong, where she served as Associate Dean (Research Higher Degrees) from 2007 to 2010 and Head of the Division of Learning, Development, and Diversity with the Faculty from 2013 to 2019. Currently, she holds the position of Chair of the University's Human Research Ethics Committee. Although she has conducted research and published papers in various areas (e.g., gifted and creative education, student development in higher education, teacher education, and the academic profession), her principal specialty has been in the field of intellectual styles. Intellectual styles – encompassing such constructs as cognitive styles, learning styles, teaching styles, and thinking styles – are people’s preferred ways of using their abilities. With an extensive academic background, she has authored numerous academic book chapters and books, including two monographs – The Malleability of Intellectual Styles (Zhang, 2013) and The Value of Intellectual Styles (Zhang, 2017), both published by Cambridge University Press. Additionally, she has authored over 150 peer-reviewed international journal and encyclopedic articles, including a substantial number as sole author. Professor Zhang is the editor-in-chief for the Oxford Encyclopedia of Educational Psychology and serves as a consulting editor for the Journal of Educational Psychology, as well as an associate editor for Educational Psychology. Furthermore, she contributes her expertise as an editorial board member for several other esteemed academic journals in the fields of psychology and education, including Educational Psychology Review; and Thinking Skills and Creativity. She has also served as an ad hoc reviewer for over 50 international peer-reviewed journals, including Cognition and Instruction, European Journal of Personality, Higher Education, Learning and Instruction, Learning and Individual Differences, Personality and Individual Differences, and Psychological Bulletin.