Prof. Zabih Ghassemlooy

Professor of Optical Communication, Emeritus Professor of Northumbria University, U.K.

Abstract

The next generation wireless communication networks (i.e., 6G and beyond) will seamlessly connect people, devices and systems together, enabling the collection, preparation, processing, storing and decision making of vast amounts of information. It is anticipated that such wireless networks will utilise different technologies for use in smart environments, including homes/buildings/cities, manufacturing, agriculture, health care, transportation systems, etc., for improving productivity and the quality of life through the efficient and sustainable resources management and use. 6G will need the convergence of different wireless technologies, assisted by machine learning to solve flexibility and scalability issues. This talk will give an overview of the emerging integrated wireless technology focusing on optical sensing, positioning and data communication within the context of 6G wireless networks and beyond, using common spectrum, device, transmission and network infrastructure to improve both spectral and energy efficiencies.

Bio

Professor Zabih Ghassemlooy (Fellow, OPTICA; Fellow, IET; Senior Member, IEEE; CEng, BSc (Hons.) MMU (1981), MSc (1984) and PhD (1987) Manchester Univ., UK. 1987-88 Post-Doctoral Research Fellow, City Univ., UK. 1988-2004 Sheffield Hallam University and 2004- Northumbria University, UK, as Associate Dean for Research and Head of Photonics Technology Laboratory and Optical Communications Research Group and now is and Emeritus Professor at Northumbria University. He was a Research Fellow (2016-2022) and a Distinguished Professor (2015-2022) at Chinese Academy of Science, a Visiting Professor at Univ. Tun Hussein Onn Malaysia (2013-17), Huaqiao Univ., China (2017-18), Technical Univ. of Prague, Czech Rep. (2019), Technical Univ. of Graz, Austria (2018), and others. He was Vice-Chairs of EU Cost-Actions IC1101 (2011-16), CA19111, 2020-24, and CA19111, 2020-2024. He is an IEEE Distinguished Lecturer for 2024-25. Has supervised 77 PhDs, 12 Research Fellows, over 1000 publications (440 journals and 8 books), and over 100 keynote/invited talks. His research interest: optical wireless communications, free space optics, visible light communications, and hybrid RF-OWC. He was Chief Editor: British J. of Applied Science and Technology and Intern. J. of Optics and Applications, and is Vice-Cahir of OSA Technical Group (Optics in Digital Systems-2018-). He was and still is involved on the editorial board of many journals including IEEE, OPTICA and IET. He is founder and chair of several international conference including IEEE/IET CSNDSP.

Prof. Arun Kumar Sangaiah

Distinguished Professor, International Grauduate School of AI, National Yunlin University of Science and Technology, Taiwan (ROC)

Abstract

The emergence of sixth-generation Internet of Things (6G-IoT) communication networks is poised to revolutionize industrial applications by enabling ultra-reliable, intelligent, and high-speed connectivity. These advancements will not only enhance automation but also drive innovation across various sectors, making industries more efficient and interconnected than ever before. Efficient communication plays a pivotal role in ensuring seamless data transmission, particularly in achieving full network coverage and supporting the rapid proliferation of IoT devices and sensors. However, the large-scale deployment of 6G-IoT networks brings forth significant challenges, including maintaining quality of service (QoS), ensuring robust security, and optimizing energy-efficient communication. Addressing these challenges is essential for unlocking the full potential of 6G technology and accelerating its adoption across industrial ecosystems. Unlike previous generations, the defining characteristic of 6G lies in its AI-powered communication, which shifts the paradigm from traditional connected devices to an ecosystem of connected intelligence. This transformation fosters a more adaptive and autonomous network environment, enabling real-time decision-making and intelligent resource management. To harness the full capabilities of 6G-IoT, leveraging AI-driven optimization, predictive analytics, and autonomous decision-making is crucial. These advanced technologies not only enhance network performance and reduce latency but also enable self-sustaining smart industries capable of operating with minimal human intervention. The keynote highlights the seamless integration of AI and 6G will be instrumental in supporting next-generation industrial applications, including real-time automation, digital twins, and intelligent manufacturing. By enabling these innovations, 6G-IoT is set to pave the way for Industry 4.0 and beyond, redefining the future of industrial connectivity and automation.

Bio

Prof. Arun Kumar Sangaiah received his Ph.D. from School of Computer Science and Engineering, VIT University, Vellore, India. He is currently a Full Professor with National Yunlin University of Science and Technology, Taiwan. He has published more than 200 research articles in refereed journals (IEEE TII, IEEE TITS, IEEE TNSE, IEEE TETCI, IEEE SysJ, IEEE SensJ, IEEE IOTJ, ACM TOSN), 11 edited books, as well as 1 patent (held and filed) and 3 projects, among two of them funded by National Science and Technology Council (NSTC), Taiwan, the Ministry of IT of India and few international projects (CAS, Guangdong Research fund, Australian Research Council) cost worth of USD 500,000 USD. Dr. Sangaiah has received many awards, Yushan Young Scholar, Clarivate Highly Cited Researcher (2021,2022, 2023), Top 2% Scientist (Standord Report-2020,2021,2022), PIFI-CAS fellowship, Top 10 outstanding researcher, CSI significant Contributor etc. Also, he is responsible for Editor-in-Chief, and Associate Editor of various reputed ISI journals. Dr. Sangaiah is a visiting scientist (2018-2019) with Chinese Academy of Sciences, China and visiting researcher of Université Paris-Est (UPEC), France (2019-2020). His Google Scholar Citations reached 27000+ with h-index of 93 and i10-index of 351.