Prof. Dr.-Ing. Daniel Sonntag

German Research Center for Artificial Intelligence, DFKI

Scientific Director of Interactive Machine Learning
 Stuhlsatzenhausweg-3, 66123 Saarbrücken &
26129 Oldenburg
Endowed Chair of Applied Artificial Intelligence, Oldenburg University 
Editor-in-Chief of the German Journal of Artificial Intelligence
Editor-in-Chief of Cognitive Technologies

His research interests include intelligent user interfaces, natural language processing, information retrieval and mining, dialogue systems, common-sense modelling, and semantic (explainable) machine learning methods for cognitive computing and improved usability.
This includes multimodal multisensor interfaces for medical and health systems and Industry 4.0 in particular, common-sense and (interactive) machine learning methods for human computer interfaces, knowledge discovery, information extraction, and cognitive modelling with ontologies.
He has published over 150 scientific articles, and has been recipient of the German High Tech Champion Award in 2011. As a principal investigator he leads both national and European projects from the Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, the Federal Ministry of Health, and Horizon 2020.
His recent application of multimodal multisensor interfaces is now having industrial impact,  for example SmartWeb's multimodal interaction design and technical infrastructure by Apple (Siri).
Publications DBLP, DFKI database, Google Scholar
Books Question Answering (SmartWeb)
Multimodal Multisensor Interfaces
News (medical systems)  News (smart factories)
  Main Projects Artificial Intelligence in Medicine
Smart Factories and Industry 4.0
Old homepage
University Courses He has been teaching since 2010 at Saarland University, the Technical University of Kaiserslautern, and Oldenburg University. 
Intelligent User Interfaces
Advances in Multimedia Information Extraction

Natural Language Access to Big Data (Fall Symposium)
Semantic Web Technologies for HCI and Information Retrieval
legal info data protection