Professor Björn W. Schuller is a distinguished leader in artificial intelligence and signal processing with profound contributions to audio intelligence and affective computing. He currently serves as Full Professor of Artificial Intelligence and Head of the Group on Language, Audio & Music at Imperial College London, as well as Full Professor and Chair of Health Informatics at the Technical University of Munich. Schuller received his diploma in electrical engineering and information technology from TUM in 1999, followed by his doctoral degree in 2006 for his pioneering research on Automatic Speech and Emotion Recognition, and completed his habilitation in 2012. His academic journey has included significant leadership roles at the University of Augsburg, where he held the Chair of Embedded Intelligence for Healthcare and Wellbeing, and positions at the University of Passau, Joanneum Research in Graz, and CNRS-LIMSI in Orsay.
Schuller's groundbreaking research has established foundational methodologies for teaching machines to understand human speech and emotional states through audio signals, catalyzing significant advances in affective computing and human-computer interaction. His work on audio feature extraction and emotion recognition algorithms has been widely adopted in both academic research and commercial applications, with his contributions to Audio Intelligence forming the technological foundation for his co-founded company audEERING. This research has enabled sophisticated emotion-aware systems that can detect subtle emotional cues in voice, revolutionizing applications in mental health monitoring, elderly care, and human-centered computing interfaces. The impact of his work extends across multiple disciplines, with extensive publications that have been widely cited in the fields of speech processing, machine learning, and healthcare technology.
As a Fellow of the ACM, IEEE, and multiple other prestigious scientific societies, Schuller has profoundly shaped the trajectory of audio intelligence research through his leadership in international collaborations and consortiums. He serves as a Core Member in the Munich Data Science Institute and Principal Investigator in the Munich Center for Machine Learning, driving interdisciplinary research at the intersection of artificial intelligence and healthcare. Schuller's vision for translating audio intelligence into real-world health applications continues to expand through his dual academic roles and entrepreneurship, with current research focusing on embedded intelligence systems for healthcare and wellbeing. His ongoing work promises to further bridge the gap between sophisticated machine learning techniques and practical healthcare solutions that can improve quality of life through intelligent audio monitoring and analysis.
