In health and medicine, an immense amount of data is being generated by distributed sensors and cameras, as well as multimodal digital health platforms that support multimedia, such as audio, video, image, 3D geometry, and text. The availability of such multimedia data from medical devices and digital record systems has greatly increased the potential for automated diagnosis. The past several years have witnessed an explosion of interest, and a dizzyingly fast development, in computer-aided medical investigations using MRI, CT, X-rays, images, point clouds, etc. This proposed workshop focuses on various multimedia computing techniques (including mobile solutions and hardware solutions) for health and medicine, which targets real-world data/problems in healthcare, involves a large number of stakeholders, and is closely connected with people's health.
This workshop focuses on various computing techniques (including mobile solutions and hardware solutions) for health and medicine. The topics of interest include (but are not limited to) the following:
Prof. Klaus Schoeffmann is an Associate Professor at the Institute of Information Technology (ITEC) at Klagenfurt University, Austria, where he received his habilitation (venia docendi) in Computer Science in 2015. His research focuses on video content understanding (including medical/surgery videos), deep learning, computer vision, multimedia retrieval, and interactive multimedia. He has secured research funding of over €2M (from FWF, KWF, and industrial partners). He has a Google H-index of 35 from over 4,000 citations to his research works, and he is founder and co-organizer of the annual Video Browser Showdown and the annual Lifelog Search Challenge. He is a member of the IEEE and the ACM, a regular reviewer for international conferences and journals in the field of multimedia and medical imaging. Klaus Schoeffmann has been the program co-chair of MMM 2021, CBMI 2021, ACM ICMR 2020, MMM2018, CMBI 2013, the demo & video co-chair of ACMMM2020, open-source software competition chair of ACMMM2019, the general co-chair of MMM2012, and the general co-chair of ACM ICMR 2024, CBMI 2025, and ACMMM2025, as well as a program co-chair of ACMMM Asia 2025.
Prof. Björn W. Schuller received the Diploma in electrical engineering and information technology in 1999, the Doctoral degree in electrical engineering and information technology for the study on automatic speech and emotion recognition in 2006, and the Habilitation degree in electrical engineering and information technology from the Technical University of Munich (TUM), Munich, Germany, in 1999, 2006, and 2012, respectively. He was an Adjunct Teaching Professorship of signal processing and machine intelligence and electrical engineering and information with TUM, in 2012. He is currently a Full Professor of artificial intelligence, the Head with The Group on Language, Audio, and Music, Imperial College London, London, U.K., Full Professor and Chair with Health Informatics, TUM Co-Founding CEO and CSO with audEERING, The Munich Data Science Institute, and The Munich Center for Machine Learning. He coauthored five books and more than 1500 publications in peer reviewed books, journals, and conference proceedings leading to more than 80,000 citations (h-index = 127). Dr. Schuller is also the President Emeritus and Fellow of the Association for the Advancement of Affective Computing, Elected Member of IEEE Speech and Language Processing Technical Committee, and Fellow of ACM, IEEE, BCS, DIRDI, and ISCA.
