Prof. Dr. Sebastian Möller
Fellow
Fellow | BIFOLD
Adjunct Professor | University of Technology Sydney
Dean | Faculty of Electrical Engineering and Computer Science, Technical University Berlin
Head | Speech and Language Technology Lab, DFKI Berlin
Professor for Quality and Usability | Technical University Berlin
Sebastian Möller was born in 1968 and studied electrical engineering at the universities of Bochum (Germany), Orléans (France) and Bologna (Italy). From 1994 to 2005, he held the position of a scientific researcher at the Institute of Communication Acoustics (IKA), Ruhr-University Bochum, and worked on speech signal processing, speech technology, communication acoustics, as well as on speech communication quality aspects. From 2005 to 2015, he worked at Telekom Innovation Laboratories, an An-Institut of TU Berlin. He was appointed Full Professor for the subject “Quality and Usability” at TU Berlin in April 2007. From 2015 to 2017, he served as a Vice Dean for Research at the Factulty for Electrical Engineering and Computer Science at TU Berlin, and from 2017 to 2019 as the Dean of this faculty. He also leads the research department “Speech and Language Technology” at the German Research Center for Artificial Intelligence, DFKI, as a Scientific Director since 2017.
Sebastian Möller received a Doctor-of-Engineering degree of Ruhr-University Bochum in 1999 for his work on the assessment and prediction of speech quality in telecommunications. In 2000, he was a guest scientist at the Institut dalle Molle d’Intélligence Artificielle Perceptive (IDIAP) in Martigny (Switzerland) where he worked on the quality of speech recognition systems. He gained the qualification needed to be a professor (venia legendi) at the Faculty of Electrical Engineering and Information Technology at Ruhr-University Bochum in 2004, with a book on the quality of telephone-based spoken dialogue systems. In September 2008, we worked as a Visiting Fellow at MARCS Auditory Laboratories, University of Western Sydney (Australia) on the evaluation of avatars. In November 2011, he was Visiting Professor at the Universidad de Granada (Spain), from Februar to April 2012 and from May to July 2014 Visiting Professor at the Ben Gurion University of the Negev in Be’er Sheva (Israel), in October 2013 Visiting Professor at NTNU in Trondheim (Norway), and from 2012 to 2018 he was Adjunct Professor at the University of Canberra (Australia). Since 2018, he is Adjunct Professor at the University of Technology Sydney (Australia). His most recent book on “Quality Engineering” was published in 2010, and his co-edited book on “Quality of Experience: Advanced Concepts, Applications and Methods” in 2014.
2009 | Johann-Philipp-Reis Award, Informationstechnische Gesellschaft im VDE |
2005 | Heisenberg Scholarship, Deutsche Forschungsgemeinschaft (DFG) |
2003 | Lothar-Cremer Award, Deutsche Gesellschaft für Akustik (DEGA) |
2001 | Preis der ITG, Informationstechnische Gesellschaft im VDE |
1998 | Förderpreis, Geers-Stiftung im Stifterverband für die Deutsche Wissenschaft |
- Speech and language technology
- Quality
- User experience
- Crowdsourcing
- Open data
Lisa Raithel, Philippe Thomas, Bhuvanesh Verma, Roland Roller, Hui-Syuan Yeh, Shuntaro Yada, Cyril Grouin, Shoko Wakamiya, Eiji Aramaki, Sebastian Möller, Pierre Zweigenbaum
Overview of #SMM4H 2024– Task 2: Cross-Lingual Few-Shot Relation Extraction for Pharmacovigilance in French, German, and Japanese
Dorothea MacPhail, David Harbecke, Lisa Raithel, Sebastian Möller
Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates
Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada, Cyril Grouin, Thomas Lavergne, Aurélie Névéol, Patrick Paroubek, Philippe Thomas, Tomohiro Nishiyama, Sebastian Möller, Eiji Aramaki, Yuji Matsumoto, Roland Roller, Pierre Zweigenbaum
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
Learning about population health from Twitter texts
Is it possible to learn about the health status of a population and potential side effect of medicationsby analyzing social media conversations? BIFOLD researchers tackled the challenge of making social media posts of medical laypersons concerning diseases and medications understandable for machines. At the BioCreative VII Challenge Evaluation Workshop 2021, they recently explored how a combination of background knowledge and a language transformer model can increase the precision of medical information extraction from Twitter texts.
An overview of the current state of research in BIFOLD
Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.