Prof. Dr. Björn Schuller
Academic Career and Research Areas
Schuller combines computer science with modern health care and medicine. The main focus lies in the acquisition, analysis, and interpretation of biosignals including in daily life, such as those generated in monitoring heart activity, metabolism, or neuronal activities. Additionally, acoustic, visual, and a variety of other parameters are also evaluated. The goal is prevention, diagnosis, as well as decision support and intervention through efficient, transparent, and trustworthy methods of current Artificial Intelligence.
Prof. Schuller received his diploma (1999), doctoral degree (2006), and habilitation (2012), all in EE/IT from TUM where he became Full Professor of Health Informatics in 2023. Since 2013 he is also with Imperial College London now as Professor of Artificial Intelligence. Further, he is the co-founding CEO and current CSO of audEERING. Previous major stays include Full Professor at the University of Augsburg (2017-2023) and University of Passau (2014-2017), and Researcher at Joanneum Research in Graz (2012) and the CNRS near Paris (2009-2010).
Awards
- IEEE Signal Processing Socitey Distinguished Lecturer (2024)
- Fellow of the ISCA (2020)
- Fellow of the IEEE (2018)
- World Economic Forum Young Scientist (2015)
- ERC Starting Grantee (2013)
Key Publications (all publications)
Eyben F, Wöllmer M, Schuller B: "openSMILE: the Munich versatile and fast open-source audio feature extractor". ACM Multimedia. Florence. 2010.
AbstractSchuller B: Intelligent Audio Analysis. Springer, 2013.
AbstractSchuller B, Batliner A: Computational Paralinguistics: Emotion, Affect and Personality in Speech and Language Processing. Wiley, 2013.
AbstractWagner J, Triantafyllopoulos A, Wierstorf H, Schmitt M, Eyben F, Schuller B, Burkhardt F: "Dawn of the transformer era in speech emotion recognition: closing the valence gap". IEEE Transactions on Pattern Analysis and Machine Intelligence. 2023; 45(9):10745–10759.
AbstractRynkiewicz A, Schuller B, Marchi E, Piana S, Camurri A, Lassalle A, Baron-Cohen S: "An investigation of the ‘female camouflage effect’ in Autism using a computerized ADOS-2 and a test of sex/gender differences". Methods. 2016; 7(10):1-8.
Abstract