Tokyo, Japan
Tokyo, Japan
Yu HUANG received his BSc from Fudan University Shanghai Medical College and a PhD from University of Cambridge. He served as the Chair Professor of Biomedical Sciences (2010-2021) in Chinese University of Hong Kong until October 2021. He is the Jeanie Hu Professor of Biomedical Sciences, Chair Professor and Head of the Department of Biomedical Sciences at City University of Hong Kong. He is the Vice President of Chinese Section of International Society for Heart Research (ISHR) and Chinese Association for Physiological Sciences. He is an elected Fellow of ISHR, International Union for Physiological Sciences Academy of Physiology, and British Pharmacological Society. He received the Inaugural Hong Kong Research Grants Council - Senior Research Fellow Award (2020). He is the first Chinese scholar to receive the Peter Harris Distinguished Scientist Award from ISHR (2024). He is an Associate Editor of Circulation Research. His team aims to elucidate cellular and molecular events in the initiation and progression of endothelial cell dysfunction in hypertension and diabetes, to uncover novel biomarkers of vascular pathogenesis, and to develop ways to reverse vascular dysfunction in animal models of cardiometabolic disease. He has co-authored 524 SCI publications including Nature, Science, Circulation Research, European Heart Journal, Cell Metabolism, PNAS, Diabetes, Hypertension, Cardiovascular Research, Kidney International etc. with over 37,250 Google scholar citations and an h-index of 99.
Hesham H. Ali is a Professor of Computer Science and the director of the University of Nebraska Omaha (UNO) Bioinformatics Core Facility. He served as the Dean of the College of Information Science and Technology at UNO between 2006 and 2021. He has been a research collaborator at Mayo Clinic Research Hospital since 2022. He has published numerous articles in various computing and informatics fields of research, including scheduling, distributed systems, data analytics, wireless networks, and Bioinformatics. He has published two books in scheduling and graph algorithms, and several book chapters in Bioinformatics. He has been serving as the PI or Co-PI of several projects funded by NSF, NIH and Nebraska Research Initiative in the areas of AI, Bioinformatics, Data Analytics and Wireless Networks. For the last 25 years, he has also been leading a Bioinformatics Research Group that focuses on developing innovative computational approaches to model complex biomedical systems and analyze big bioinformatics data using AI tools, Network models, and graph algorithms. The research group is currently developing next generation data analytics tools for analyzing large heterogeneous biological and health data associated with various biomedical research areas, particularly projects associated with infectious diseases, microbiome studies, early childhood development and aging research. He has led many local and national outreach initiatives, including Bioinformatics training workshops, Women in IT initiatives, IT education and training programs, and IT summer internship camps.odels can leverage the new biomarkers in supporting advanced biomedical research and lead to the next generation of healthcare.
Eastern Institute of Technology
De-Shuang Huang is a Professor/Director in Ningbo Key Laboratory of Multi-Omics & Multimodal Biomedical Data Mining and Computing, Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo, China. He is currently Foreign Academician of Russian Academy of Engineering, the Fellow of the IEEE (IEEE Fellow), the Fellow of the International Association of Pattern Recognition (IAPR Fellow), the Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA), Fellow of the International Artificial Intelligence Industry Alliance (AIIA), and associated editors of IEEE/ACM Transactions on Computational Biology & Bioinformatics and IEEE Transactions on Cognitive and Developmental Systems, etc. He founded the International Conference on Intelligent Computing (ICIC) and the International Conference on Applied Intelligence (ICAI) in 2005 and 2023, respectively. He also served as the 2015 International Joint Conference on Neural Networks (IJCNN2015) General Chair, July12-17, 2015, Killarney, Ireland, the 2014 11th IEEE Computational Intelligence in Bioinformatics and Computational Biology Conference (IEEE-CIBCBC) Program Committee Chair, May 21-24, 2014, Honolulu, USA. He has published over 480 papers in international journals, international conferences proceedings, and book chapters. Particularly, he has published over 260 SCI indexed papers. His Google Scholar citation number is over 25815 times and H index 84. His main research interest includes neural networks, pattern recognition and bioinformatics. His main research interest includes neural networks, pattern recognition and bioinformatics.
Nara Prefectural University, Japan
Dr. Arata SUZUKI earned his Ph.D. in Information Science from Nara Institute of Science and Technology. Since 2021, he has been a professor at Nara Prefectural University, and in 2024, he became the Dean of faculty of area promotion. His career includes positions at Zojirushi Corporation and Wakayama University. Dr. Suzuki’s research focuses on statistical data analysis, Taguchi robust engineering, and biomedical data analysis. He is particularly dedicated to developing health assessment methods based on bio-signal analysis, with a special emphasis on photoplethysmography for health evaluation.
Speech Title: " Digital Medicine and Image Processing: The Past and Future"
Abstract: Due to the global shortage of medical professionals, the importance of Digital Medicine and Image Processing is increasing. New technologies are being developed to assist medical professionals, such as electronic medical records, IoT healthcare devices, and medical image diagnosis using AI. At the same time, digital medicine is also being used to support health in everyday life. One technology that everyone uses is the pedometer on their smartphone. These are used in health promotion insurance, where insurance premiums vary depending on the number of steps walked in a day. In this presentation, we will focus on the use of digital devices in our everyday lives, look back on the technology so-called Digital Medicine has developed so far, and discuss future prospects.
Beijing Language and Culture University, China
XiWen Zhang is currently a full professor of Digital Media Department, School of Information Science, Beijing Language and Culture University. Prof. Zhang worked as an associated professor from 2002 to 2007 at the Human-computer interaction Laboratory, Institute of Software, Chinese Academy of Sciences. From 2005 to 2006 he was a Post doctor advised by Prof. Michael R. Lyu in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. From 2000 to 2002 he was a Post doctor advised by Prof. ShiJie Cai in the Computer Science and Technology department, Nanjing University. Prof. Zhang's research interests include pattern recognition, computer vision, and human-computer interaction, as well as their applications in digital image, video, and ink. Prof. Zhang has published over 60 refereed journal and conference papers. His SCI papers are published in Pattern Recognition, IEEE Transactions on Systems Man and Cybernetics B, Computer-Aided Design. He has published more than twenty EI papers. Prof. Zhang received his B.E. in Chemical equipment and machinery from Fushun Petroleum Institute (became Liaoning Shihua University since 2002) in 1995, and his Ph.D. advised by Prof. ZongYing Ou in Mechanical manufacturing and automation from Dalian University of Technology in 2000.
Speech Title: "Three Views on Intelligently Extracting and Generating Information from Image"
Abstract: Due to pattern recognition and deep learning, various information can be extracted and generated from image. Our work has focused on using the proposed hierarchy models, local homogeneity, and adversarial generation. Various digital images are processed, such as ones scanned from mechanical paper drawings and paper text, face images, portrait ones with line drawings, and microscopic bone marrow images. Various information is extracted using the proposed hierarchy models. Graphics and their multi-levels compounded objects are extracted and recognized from images scanned from mechanical paper drawings using a hierarchy model of engineering drawings. Faces and their components are extracted from photos using a facial model. Various information is extracted using the proposed local homogeneity. Karyocytes and their components from microscopic bone marrow images based on regional color features. Various information is extracted and generated from image using cycle-Consistent adversarial networks. Text is separated from grid background using cycle-Consistent adversarial networks. Digital images of Chinese classical upper-class lady paintings are generated from images with line drawings using conditional generative adversarial networks.
