Titles (selected): | Univ.-Prof. (TUM/University of Augsburg), Professor (Imperial College London/VGTU), Dr.-Ing. (TUM) habil. (TUM) Dipl.-Ing. univ. (TUM), Visiting Professor (HIT), Honorary Dean (TJNU), Fellow AAAC, FBCS, FIEEE, Fellow ISCA |
Fields: | Artificial Intelligence, Machine & Deep Learning; Audio, Language, Bio & Multimedia Signal Processing; Health Informatics, mHealth, Affective Computing; Computer Ethics |
Affiliated with: | Technical University of Munich (Medicine), Imperial College London (Computing), University of Augsburg (Informatics/Medicine), audEERING GmbH, Harbin Institute of Technology, Tianjin Normal University |
Alma Mater: | Technische Universität München (EE/IT) |
Activity (selected): | Field Chief Editor Frontiers in Digital Health and Health Technologies Editor in Chief AI Open Journal Editor in Chief IEEE Transactions on Affective Computing General Chair IEEE ACII 2019, IEEE ACII Asia 2018, ACM ICMI 2014 Program Chair Interspeech 2019, ACM ICMI 2019 and 2013, IEEE/AAAC ACII 2015 and 2011, IEEE SocialCom 2012 Coordinator European Project EngageMe, European Project ASC-Inclusion Principal Investigator ERC Starting Grant iHEARu Principal Investigator DFG Reinhart Koselleck Grant AUDI0NOMOUS President-Emeritus (Secretary) of the AAAC |
Google Scholar: | Profile (currently >60,000 citations, h-index >110) |
Code and Data: | openaudio.eu |
Scientific Papers: | (currently >1500, >300 in journals) – download the full publication list as PDF or from overleaf. |
Five Recent Articles: | H. Coppock, L. Jones, I. Kiskin, and B. Schuller, “COVID19 Detection from Audio: Seven Grains of Salt,” The Lancet Digital Health, vol. 3, pp. e537–e538, 9 2021. B. Schuller, “Speech Emotion Recognition: 20 Years in a Nutshell, Benchmarks, and Ongoing Trends,” Communications of the ACM, vol. 61, pp. 91–99, May 2018. M. Littmann, K. Selig, L. Cohen, Y. Frank, P. Honigschmid, E. Kataka, A. Mosch, K. Qian, A. Ron, S. Schmid, A. Sorbie, L. Szlak, A. Dagan-Wiener, N. Ben-Tal, M. Y. Niv, D. Razansky, B. W. Schuller, D. Ankerst, T. Hertz, and B. Rost, “Validity of machine learning in biology and medicine increased through collaborations across fields of expertise,” Nature Machine Intelligence, vol. 2, 2020. 12 pages. O. Rudovic, J. Lee, M. Dai, B. Schuller, and R. W. Picard, “Personalized machine learning for robot perception of affect and engagement in autism therapy,” Science Robotics, vol. 3, June 2018, AAAS, 12 pages G. Trigeorgis, M. A. Nicolaou, S. Zafeiriou, B. Schuller, “Deep Canonical Time Warping for simultaneous alignment and representation learning of sequences,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, pp. 1128– 1138, May 2018. |
Granted Patents (selected) | C. Joder, F. Weninger, B. Schuller, and D. Virette, “Method and Device for Reconstructing a Target Signal from a Noisy Input Signal”, CN104685562B/EP2877993B1/US9536538B2/WO2014079483A1, Chinese/European/US/World patent, 2012. C. Joder, F. Weninger, B. Schuller, and D. Virette, “Method for Determining a Dictionary of Base Components from an Audio Signal, EP2912660B1, European patent, 2012. |
Sport Degress (selected): | Black Belt 3. Dan Tae Kwon Do (ITF, Chae-Yong Song, div. Masters) Black Belt 2. Dan Tang Soo Do (WTSDA, Jae Chul Shin, Master: Klaus Trogemann) Master Applicant 2ème GB Savate-Boxe Française (Dojo de Grenelle, Master: Alain Formaggio) Gold Level Ballroom Dancing (ADTV, TTC Munich Pasing and others) Lead (Rock) Climbing License (DAV) |
Musical Instruments (selected): | diverse Guitars/Mandolins, Piano/Keyboards, diverse Flutes/Harmonicas, Cajon |
Languages (selected): | German, English, French, Chinese, Italian (basic), Russian (basic) |