Abstract

Higher Education is faced with enormous challenges : emergence of competitive for-profit education industries, decreasing population in advanced societies, and the introduction of AI in various stages of education. The rapidly changing risks should be handled with in-depth knowledge as well as timely decisions on how to transform the goals and missions, organizational structure, degree diversity, financing options at higher education in general. In this talk, the current trends and the best practices of edutech for higher education will be examined. As an example, Hallym university’s short and long-term strategies to become the most innovative and AI-friendly university in the world, will be presented.

Biography

Yanghee Choi received B.S. in electronics engineering from Seoul National University, M.S. in electrical engineering from Korea Advanced Institute of Science, and Doctor of Engineering in Computer Science from Ecole Nationale Superieure des Telecommunications (ENST) in Paris, in 1975, 1977 and 1984 respectively. Before joining the School of Computer Science and Engineering, Seoul National University in 1991, he has been with Electronics and Telecommunications Research Institute (ETRI) during 1977-1991.

He was president of Open Systems and Internet Association of Korea. He was president of Korean Institute of Information Scientists and Engineers. He was also dean of Graduate School of Convergence Science and Technology, and president of Advanced Institutes of Convergence Technology. He was the chair of Future Internet Forum, and vice-chair of Asia Future Internet Forum. He was chairman of Samsung Science and Technology Foundation (www.samsungstf.or.kr). From July 2014 until July 2017, he worked at the Korean government as Minister of Science, ICT and Future Planning. He was chair of Seoul National University’s AI Committee during 2017-2020. Since 2021, Choi serves as the president of Hallym University in Chuncheon, Korea. He is a member of National Academy of Engineering, National Academy of Science and Engineering.

Abstract

In this keynote we will examine a phenomenon that can resignify communication networks as we know them. Instead of acting just as a data transport medium, multiple technologies have made it possible to leverage networks to run and provide user-level services. This paradigm has been alternately called Computing In the Network (COIN) and In-Network Computing (INC). INC has been mostly used in the context of programmable hardware, which provides support for the implementation of services on the data-layer level. Network Functions Virtualization (NFV) is another alternative technology to deploy novel types of services within the network. NFV allows the implementation in software of middleboxes traditionally available as specialized hardware. Network services can be implemented as SFCs (Service Function Chains) based on virtualization technologies that run on commodity hardware. Although most virtualized functions have classic middlebox functionalities (e.g. firewalls or intrusion detectors) arbitrary COIN services can be implemented using NFV technologies, which we call NFV-COIN. An NFV-COIN architecture has been proposed and published as an IETF Draft. We present case studies of NFV-COIN services for distributed abstractions that are notoriously relevant and hard to implement and maintain, including consensus, reliable and ordered broadcast, and failure detectors.

Biography

Elias P. Duarte Jr. is a Full Professor at Federal University of Parana, Curitiba, Brazil, where he is the leader of the Computer Networks, Distributed Systems & Security Lab (LaRSiS). He has been twice (2005 and 2009) Visiting Associate Professor at Tohoku University (Japan) and Visiting Researcher at the University of California at Irvine (1997). His research interests include Computer Networks and Distributed Systems, their Dependability, Management, and Algorithms. He has published over 300 peer-reviewer papers and has supervised more than 130 students both on the graduate and undergraduate levels. Prof. Duarte has been Associate Editor of the Computing (Springer) journal and IEEE Transactions on Dependable and Secure Computing, and has served as chair of 30 conferences and workshops in his fields of interest, including chairing TCPs of SRDS'18, ICDCS'21, and GLOBECOM'24. He received a Ph.D. degree in Computer Science from Tokyo Institute of Technology, Japan, 1997, M.Sc. degree in Telecommunications from the Polytechnical University of Madrid, Spain, 1991, and both BSc and MSc degrees in Computer Science from Federal University of Minas Gerais, Brazil, 1987 and 1991. He chaired the Brazilian National Laboratory on Computer Networks (2012-2016). He is a member of the IFIP WG 10.4 on Dependable Computing & Fault Tolerance, member of the Brazilian Computing Society (SBC) and a Senior Member of the IEEE.

Abstract

TBA

Biography

Dr. Chong-Kwon Kim received BS degree and MS degrees in Industrial Engineering from the Seoul National University and the Georgia Institute of Technology, respectively. He then switched his specialties and received his Ph.D degree in Computer Science from the University of Illinois at Urbana-Champaign. He is currently a Distinguished Professor at Korea Institute of Energy Technology (KENTECH). He is serving on a Director of Research Institute of Energy AI at KENTECH, focusing on the integration of AI technology into various problems in energy area. Before KENTECH, he has worked as an MTS at Bell Communications Research from 1987 to 1991 and as a professor at the Seoul National University from 1991 to 2021. During his 30 plus more career, he published more than 100 research papers in the field of computer network, performance analysis, machine learning, data mining and machine learning. He has served on a president of Korea Institute of Information Scientists and Engineers during 2014 and 2015 and has been serving on steering committee of several international conferences. His research interests include machine learning and its applications to energy systems.

Abstract

The RAN intelligent controller (RIC) is cloud native and a central component of an open and virtualized RAN network. The RIC enables to deployment of machine learning and AI techniques to optimize resources and services in the RAN. Thus, it is an important component that brings intelligence, agility, and programmability to the radio access network. On the other hand, semantic communication has emerged as a new communication paradigm that aims at the successful transmission of semantic information conveyed by the transmitter rather than the accurate reception of each single bit regardless of the meaning. With semantic communication, it is likely that some form of intelligence is needed at the RAN to enable such a paradigm. In this talk, we will share how RIC is going to enable semantic communications to become reality. Furthermore, we will also share some initial work in this area through Singapore’s first national Future Communications Research and Development Programme (FCP).

Biography

Tony Q. S. Quek received the B.E. and M.E. degrees in Electrical and Electronics Engineering from Tokyo Institute of Technology, respectively. At Massachusetts Institute of Technology, he earned the Ph.D. in Electrical Engineering and Computer Science. Currently, he is the Cheng Tsang Man Chair Professor with Singapore University of Technology and Design (SUTD) and ST Engineering Distinguished Professor. He also serves as the Head of ISTD Pillar, Director for Future Communications R&D Programme, Sector Lead for SUTD AI Program, and the Deputy Director of SUTD-ZJU IDEA. His current research topics include wireless communications and networking, 6G, network intelligence, non-terrestrial networks, and open radio access network.

Dr. Quek is currently serving as an Area Editor for the IEEE Transactions on Wireless Communications. He was an Executive Editorial Committee Member of the IEEE Transactions on Wireless Communications, an Editor of the IEEE Transactions on Communications, and an Editor of the IEEE Wireless Communications Letters. He received the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the 2012 IEEE William R. Bennett Prize, the 2016 IEEE Signal Processing Society Young Author Best Paper Award, the 2017 CTTC Early Achievement Award, the 2017 IEEE ComSoc AP Outstanding Paper Award, the 2020 IEEE Communications Society Young Author Best Paper Award, the 2020 IEEE Stephen O. Rice Prize, the 2020 Nokia Visiting Professorship, and the the 2022 IEEE Signal Processing Society Best Paper Award. He is an IEEE Fellow, a WWRF Fellow, and a Fellow of the Academy of Engineering Singapore.

Abstract

Generative AI has emerged as a promising technology not only to generate creative contents such as text (ChatGPT), images (Dall-E), and video (Sora) but also to analyze and optimize computing and networking systems. In this presentation, we present applications of generative AI in network optimization. Firstly, we introduce general concepts and background of generative AI models and their capabilities. Next, we consider two generative AI technologies, i.e., large language models (LLMs) and generative diffusion models (GDMs). We explore the integration of LLMs into the next-generation networks, focusing on how implicit and explicit interactions can enhance network functionality, improve user experience, and promote efficient network management. Subsequently, we propose an LLM-enabled network management and optimization framework, to generate network management formulation. Moreover, we use GDM to solve the network management formulation through the deep reinforcement learning. Finally, we outline several important research directions.

Biography

Dusit Niyato is currently a President's Chair Professor in the College of Computing & Data Science (CCDS), Nanyang Technological University, Singapore. He received B.E. from King Mongkuk’s Institute of Technology Ladkrabang (KMITL), Thailand in 1999 and Ph.D. in Electrical and Computer Engineering from the University of Manitoba, Canada in 2008. Dusit's research interests are in the areas of mobile generative AI, edge intelligence, quantum computing and networking, and incentive mechanism design. Dusit won the IEEE Vehicular Technology Society Stuart Meyer Memorial Award. Dusit won the IEEE Vehicular Technology Society Stuart Meyer Memorial Award. Currently, Dusit is serving as Editor-in-Chief of IEEE Communications Surveys and Tutorials (impact factor of 34.4 for 2023) and will serve as the Editor-in-Chief of IEEE Transactions on Network Science and Engineering (TNSE) from 2025. He is also an area editor of IEEE Transactions on Vehicular Technology (TVT), topical editor of IEEE Internet of Things Journal (IoTJ), lead series editor of IEEE Communications Magazine, and associate editor of IEEE Transactions on Wireless Communications (TWC), IEEE Transactions on Mobile Computing (TMC), IEEE Wireless Communications, IEEE Network, IEEE Transactions on Information Forensics and Security (TIFS), IEEE Transactions on Cognitive Communications and Networking (TCCN), IEEE Data Descriptions, IEEE Transactions on Services Computing (TSC), and ACM Computing Surveys. He was also a guest editor of IEEE Journal on Selected Areas on Communications. Dusit is the Members-at-Large to the Board of Governors of IEEE Communications Society for 2024-2026. He was named the 2017-2023 highly cited researcher in computer science. He is a Fellow of IEEE and a Fellow of IET.