Hui Li, Professor at Peking University and Chief Information Scientist of IASTIC. He is a Foreign Academician of the Russia Academy of Natural Sciences, a Member of the Expert Committee of the World Digital Tech. Academy (WDTA) under the UN, an IET Fellow, and a Senior Member of IEEE and CCF. He received his B.Eng. and M.S. degrees from Tsinghua University and his Ph.D. from The Chinese University of Hong Kong. He previously served as Director of the Shenzhen Key Lab of Information Theory & Future Internet Architecture, and Director of the PKU Lab for the China Environment for Network Innovations (CENI), a National Major Research Infrastructure.

Prof. Li proposed "MIN", the world’s first co-governing future network architecture based on blockchain technology, and successfully implemented its prototype on an operator's network, which won the "World Leading Internet Scientific and Technological Achievements" award at the 6th World Internet Conference in 2019. He authored the world's first English monograph themed "Cyberspace UN," published by Springer. His research interests include network architecture, cyberspace security, blockchain, and distributed storage, fields in which he has published four monographs as the first author.

Prof. Dr. Bedir Tekinerdogan is a computer scientist with more than 30 years of experience in software engineering, systems engineering, and information technology. He is a Full Professor and Chair of the Information Technology Group at Wageningen University & Research, and holds MSc and PhD degrees in Computer Science from the University of Twente, the Netherlands. He is recognized among the Stanford/Elsevier World’s Top 2% Scientists and has authored more than 500 scientific publications and edited 15 academic books. His work focuses on software and systems architecture, product line engineering, model-based systems engineering, data science, and AI-enabled systems. He has contributed to large-scale industrial and research projects in domains including automotive systems, cyber-physical and defense systems, precision agriculture, smart farming, and energy systems. His current research addresses AI for software/systems engineering and software/systems engineering for reliable, explainable, and trustworthy AI-enabled systems.

Title: Architecting Distributed Learning Ecosystems

Abstract:Artificial intelligence is increasingly moving beyond isolated models and centralized training pipelines. Machine learning now takes place within broader ecosystems that include data, models, platforms, edge devices, digital twins, agents, organizations, and humans. This is visible in areas such as healthcare, agriculture, autonomous systems, smart industry, and software engineering, where data is often distributed across different locations and stakeholders. Bringing all data to a single central place is not always feasible due to privacy, ownership, regulation, latency, bandwidth, and domain-specific constraints. This keynote focuses on how we can architect such distributed learning ecosystems. Rather than focusing solely on individual machine learning algorithms, the talk considers the larger system in which learning occurs. This includes edge-cloud infrastructures, federated learning, digital twins, AI agents, and cross-organizational collaboration. From this perspective, architecture plays an important role in enabling scalability, reuse, interoperability, trustworthiness, explainability, and lifecycle management. The keynote brings together insights from artificial intelligence, software architecture, systems engineering, and AI engineering. The central message is that the future of AI will be shaped not only by larger and more powerful models, but also by our ability to design adaptive, reusable, and responsible learning ecosystems that are aligned with real-world needs. In this sense, distributed learning is not only a technical challenge, but also an architectural and socio-technical challenge.

Lei Chen received the B.Sc. and M.Sc. degrees in electrical engineering from Shandong University, Jinan, China, and the Ph.D. degree in electrical and computer engineering from University of Ottawa, Ontario, Canada. He is currently an Associate Professor with the School of Information Science and Engineering, Shandong University, China. His research interests include image processing and computer vision, visual quality assessment and pattern recognition, machine learning and artificial intelligence. He was the principal investigator of projects granted from the National Natural Science Foundation of China, National Natural Science Foundation of Shandong Province, China Postdoctoral Science Foundation, etc. He has published more than60 papers on top international journals and conferences in recent years including IEEE TIP, Signal Process., ICME, etc. He was awarded the Future Plan for Young Scholars of Shandong University. He served for many international conferencesasProgram Chair,Technical Chair or Publicity Chair.