Prof. Zhihua Zhou (IEEE/ACM/AAAI/AAAS Fellow, member of the Academia Europaea)
Nanjing University, China

Bio: Zhi-Hua Zhou is Professor of Computer Science and Artificial Intelligence, Vice President of Nanjing University. His research interests are mainly in machine learning and data mining, with significant contributions to ensemble learning, multi-label and weakly supervised learning, etc. He has authored the books "Ensemble Methods: Foundations and Algorithms", "Machine Learning", etc., and published more than 200 papers in top-tier journals or conferences, with more than 90,000 citations according to Google Scholar. Many of his inventions have been successfully deployed in industry. He founded ACML (Asian Conference on Machine Learning), serves as series editor of Springer Lecture Notes in Artificial Intelligence, advisory board member of AI Magazine, editor-in-chief of Frontiers of Computer Science, associate editor of AIJ, MLJ, etc. He is President of IJCAI Trustee, Fellow of the ACM, AAAI, AAAS, IEEE, member of the Academia Europaea, and recipient of the National Natural Science Award of China, the IEEE Computer Society Edward J. McCluskey Technical Achievement Award, the CCF-ACM Artificial Intelligence Award, etc.

Prof. Ryuji Kohno (IEICE Life/IEEE Fellow)
Yokohama National University, Japan

Bio: Ryuji Kohno received the Ph.D. degree from the University of Tokyo in 1984. He was a Professor and the Director of Centre on Medical Information and Communication Technology, in Yokohama National University (YNU) in Japan for 1998-2021 and then Professor Emeritus of YNU teaching in Toyo University. In his currier he played a part-time role of a director of Advanced Telecommunications Laboratory of SONY CSL during 1998-2002, directors of UWB Technology and medical ICT institutes of NICT during 2002-2012. For 2012-2020 he was CEO of University of Oulu Research Institute Japan - CWC-Nippon Co. and since 2020 Vice-President of YRP International Alliance Institute. The meanwhile for 2007-2020 a distinguished professor in University of Oulu in Finland and since 2006 a member of the Science Council of Japan. In IEEE he was a member of the Board of Governors of Information Theory Society in 2000-2009, and editors of Transactions on Communications, Information Theory, ITS, IEEE802.15 standardization TG6ma Chair, and IEEE Life Fellow. In IEICE he was a vice-president of Engineering Sciences Society of IEICE during 2004-2005, Editor-in chief of the IEICE Trans. Fundamentals during 2003-2005, and IEICE Fellow. He is a founder and a chair of steering committee of international symposia of medical information and communication technologies (ISMICT) since 2006. He has played a role of member in radio regulatory committee of the Ministry of Internal affairs and Communications (MIC) Japan and ITU-R.

Speech Title: "Sustainable R&D and Business Promotion of the Universal Platform among Interactive Machine Learning, 6G, and Dependable Wireless BAN for Human, Vehicular, Robotic and Other Bodies"

Abstract: In a medical healthcare field, wireless body area network (BAN) has a huge potential to create innovation by promoting integrated research and development with cloud networks and data science such as integrated BAN/6G/AI platform. A new international standard of WBAN with enhanced dependability, IEEE802.15.6ma has been extended to car and robotic bodies from human body to promote a global social service and business toward goals of SDGs. To achieve the goals it is necessary to approach any other technologies such as data science, metaverse, security, quantum, AI/ML computing, chat GPT, DX, etc. with WBAN. This talk focuses on comprehensive research, development, standard, regulation, field trials, business, and social services of the universal platform with advanced information communication technology (ICT) and AI data science to achieve sustainable medical healthcare and other SDGs. 6G infrastructure networks could be applied with dependable WBAN and machine-learning with data mining for medical social platform using interactive reliable data and cognitive control. Particularly some projects on brain-machine-interface (BMI) and elderly people day care using ultra-wide band(UWB) WBAN and multimodal machine-learning with various sensed data are introduced. To manage make comprehensive design and operation of such a universal platform is not so easy but a key for sustainable success. This talk addresses latest business promotion with clinical trials, latest activity of IEEE802 Dependable BAN and ETSI Smart BAN, and regulation update with regulatory scientific approach, and bigger market of the universal platform in automotive industry, social infrastructure maintenance, etc. Moreover, education of such a balanced expert for multidisciplinary fields could be covered.

Prof. Guoping Qiu
The University of Nottingham, UK & The University of Nottingham Ningbo, China

Bio: Professor Guoping Qiu researches neural networks and their applications in image processing. He pioneered application of neural networks to image feature extraction, introducing one of the earliest representation learning methods that leveraged unsupervised competitive neural networks for image representation. He also spearheaded learning-based super-resolution techniques and developed early neural network solutions for compression artifact removal, well before deep learning became mainstream in these applications. Professor Qiu has been at the forefront of HDR imaging, pioneering tone-mapping methods that have fundamentally transformed how HDR content is processed and displayed. Innovations from his research group have been successfully transferred to award-winning digital photo editing software such as HDR Darkroom and Fotor, which are used by hundreds of millions of consumers worldwide. His recent research focuses on deep learning, visual-language modeling, and large language models (LLMs), applying these cutting-edge technologies to some of the most complex challenges in digital imaging. As Chief Scientist at Everimaging (www.everimaging.com), the company behind HDR Darkroom and Fotor, he is driving advancements in imaging technologies to solve real-world problems. With a distinguished career spanning academia and industry, Professor Qiu’s contributions have had a lasting impact on both fundamental research and real-world applications in imaging technology.

Professor Qiu currently holds the position of Chair Professor of Visual Information Processing at the School of Computer Science, University of Nottingham, UK. Additionally, he serves as the Vice Provost for Education and Student Experience at the University of Nottingham Ningbo China (UNNC), overseeing the education and student experience of a diverse academic community of over 10,000 students and 1,000 staff from more than 70 countries and regions. UNNC delivers all its teaching in English and offers undergraduate, Master's, and PhD programs across business, humanities, social sciences, and science and engineering, awarding degrees from the University of Nottingham.