Prof. Dr. Ute Schmid
Head of Cognitive Systems Group
Office hours: by appointment
Phone: +49-951-863 2860
Ute Schmid holds a diploma in psychology and a diploma in computer science, both from Technical University Berlin (TUB), Germany. She received her doctoral degree (Dr. rer.nat.) in computer science from TUB in 1994 and her habilitation in computer science in 2002. From 1994 to 2001 she was assistant professor (wissenschaftliche Assistentin) at the Methods of AI/Machine Learning group, Department of Computer Science, TUB. Afterwards she worked as lecturer (akademische Rätin) for Intelligent Systems at the Department of Mathematics and Computer Science at University Osnabrück and was member of the Cognitive Science Institute. Since 2004 she holds a professorship of Applied Computer Science/Cognitive Systems at the University of Bamberg. In December 2019 Ute Schmid has been elected as a board member of the Bavarian Institute of Digital Transformation. She is a fortiss research fellow and member of the Steering Committee of the IBM fortiss Center for AI. She serves as representant for the CLAIRE National Contact Point Germany. Ute Schmid dedicates a significant amount of her time to measures supporting women in computer science and to promote computer science as a topic in elementary, primary, and secondary education. She won the Minerva Award of Informatics Europe for her university. Currently, Ute Schmid is engaged in educating the public about artificial intelligence in general and machine learning and she gives workshops for teachers as well as high-school students about AI and machine learning (see Talks).
Research interests of Ute Schmid are mainly in the domain of comprehensible machine learning, explainable AI, and high-level learning on relational data, especially inductive programming. Research topics are generation of visual, verbal and example-based explanations, cognitive tutor systems, cooperative and interactive learning, knowledge level learning from planning, learning structural prototypes, analogical problem solving and learning. Further research is on various applications of machine learning (e.g., classifier learning from medical data and for facial expressions) and empirical and experimental work on high-level cognitive processes. Ute Schmid is a pioneer of Computer Science for Primary School (FELI) and is engaged in the domain of AI education.
- For media coverage and other miscellaneous information see News
- For outreach talks about AI and machine learning see Talks
- Board member of the Bavarian Institute of Digital Transformation
- fortiss research fellow with special topic inductive programming and member of the Steering Committee of the IBM fortiss Center for AI (see Robust AI project)
- Representant for CLAIRE National Contact Point Germany
- Chair of KI 2020
- Organizer of the seminar series Approaches and Applications of Inductive Programming (AAIP)
- Organizer of the First European Workshop on Cognitive Modeling (1996), now International Conference on Cognitive Modeling (ICCM)
- Dean of the Faculty (Oct 2017-Sept 2019)
- Elected women's representative of the Dept. of Information Systems and Applied Computer Science, Bamberg University (since January 2005, during time as dean vice representative) -- winner of the Minvera Award of Informatics Europe 2018
- Initiation, organization and executionOrganizer of annual Girls and Computer workshops (MuT), Organizer of GirlsDay
- Initiation, organization and execution of the childern and high-school students program of the faculty: WIAI-Nachwuchs (since 2008)
- Former board member of the German Cognitive Science Society
- Former member of the editorial board of Künstliche Intelligenz, now member of the advisory board
Ute Schmid has teaching experience in artificial intelligence, algorithms and programming languages, human-computer interaction, cognitive science, and cognitive psychology. Since 2004 she holds lectures in artificial intelligence, machine learning and cognitive modeling. She offers a special course "Kognitive Informatik" for students of psychology, as well as a seminar on gender aspects in computer science. In seminar courses and projects she covers topics of inductive programming, human-level learning, and explainable AI.