Prof. Björn W. Schuller

Technische Universität München (TUM), Germany

IEEE & ACM Fellow

Research Areas: Computer audition, affective computing, and health informatics

Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany where he is Full Professor and Chair of Health Informatics.   He is also Full Professor of Artificial Intelligence and the Head of GLAM at Imperial College London/UK, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, Core Member in the Munich Data Science Institute (MDSI), Principal Investigator in the Munich Center for Machine Learning (MCML), Fellow of the Imperial Data Science Institute,   and permanent Honorable Dean at TJNU/China and Visiting Professor at HIT/China amongst other Professorships and Affiliations.   Previous stays include Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, independent research leader within the Alan Turing Institute as part of the UK Health Security Agency, Guest Professor at Southeast University in Nanjing/China, Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. 

Prof. Ram Bilas Pachori

Indian Institute of Technology Indore, India

Fellow of IET, IETE (India), IEI (India), IEEE Senior Member

Research Areas: Signal and image processing, biomedical signal processing, non-stationary signal processing, speech signal processing, brain-computer interface, machine learning, and artificial intelligence and the internet of things in healthcare.

He was an Associate Editor of IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021-2024). Currently, he is an Associate Editor of Electronics Letters, IEEE Open Journal of Engineering in Medicine and Biology, Computers and Electrical Engineering, and Biomedical Signal Processing and Control. He is also serving as a Handling Editor of Signal Processing and an Editor of IETE Technical Review journal. He is a Fellow of IETE, IEI, and IET. He has authored the textbook titled “Time Frequency Analysis Techniques and their Applications” (CRC Press, 2023). He has supervised 21 Ph.D. theses(12 Ph.D. theses under progress). He has 352 publications, which include journal articles (220), conference papers (91), books (11), and book chapters (30). He has also eight patents, including two granted (Australian patent and Indian patent) and six published (Indian patents). His publications have been cited approximately17500 times with h-index of 72 according to Google Scholar.

Prof. Ye Li

Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), China

IET Fellow

Research Areas: Wearable sensing and health big data analysis technology.

Li Ye, Ph.D., Researcher, doctoral supervisor. Director of Digital Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Director of Biomedical Information Technology Research Center, Deputy director of Key Laboratory of Health Informatics, Chinese Academy of Sciences, Director of National and Local Joint Engineering Research Center of Health Big Data Intelligent Analysis Technology, leading talent of Science and Technology Innovation in Guangdong Province, A Class talent of Shenzhen Peacock Program, Shenzhen Pengcheng Scholar. British Institute of Engineering and Technology (IET Fellow), Royal Society of Public Health (RSPH Fellow), WHO digital health information system guide expert, was selected as the world's top 2% scientists in 2021. In 2008, he returned to China as a full-time imported talent to work in Shenzhen Advanced Institute of Chinese Academy of Sciences and established a health informatics cross team. In recent years, focusing on wearable sensing and health big data analysis technology, he has published more than 160 articles, including more than 60 SCI retrieval papers and more than 30 IEEE journal papers. He was the editorial board member of Information Fusion (IF=17.564) and the editor and Physiological editor of the IEEE Journal of Biomedical and Health Informatics (IF=7.021) for two consecutive years Editor of Measurement (IF=2.688) journal, member of organizing committee or Branch Chair of IEEE/ACM important international conferences in the field of pervasive computing and biomedical information technology, such as PICom, BodyNet, EMBC, BSN&BHI, UIC, etc. 

Prof. Nic James

London Sport Institute, Middlesex University, UK

Research Areas: Sports Performance Analysis: Methodoligcal approaches

Nic is a well-known researcher in sports performance analysis having worked mainly in academic settings but also in elite sport. Nic has developed a number of academic courses in performance analysis, motor learning and statistics from undergraduate to postgraduate level. He helped develop a Sports Science degree at Swansea University before leading the MSc in Performance Analysis at both Cardiff Metropolitan and Middlesex Universities. Nic is currently head of research for the London Sport Institute and currently spends much of his time supervising PhD students and teaching at Masters Level. His research interests primarily relate to understanding sports performance with a view to informing practice. To enable this he has become familiar with advanced statistical methods using a range of software to present research findings in visually descriptive ways.