Prof. Dr. Ute Schmid
Head of Cognitive Systems Group
Lehrstuhl für Kognitive Systeme
Office: WE5/05.043
Office hours: by appointment
Phone: +49-951-863 2860
Email: ute.schmid(at)uni-bamberg.de
Ute Schmid is head of the chair for cognitive systems at University of Bamberg. She 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. In 2004 she became professor of Applied Computer Science/Cognitive Systems at the University of Bamberg. In 2022 Ute Schmid was elected as EurAI fellow. She is a fortiss research fellow and member of the Steering Committee of the IBM fortiss Center for AI. Since 2020 she is member of the board of directors of the Bavarian Insistute of Digital Transformation (bidt). Ute Schmid is also a member of the Bavarian AI Council (Bayerischer KI-Rat). Furthermore, since 2020 Ute Schmid is head of the Fraunhofer IIS project group Comprehensible AI (CAI). 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 Gender Equality Award of Informatics Europe 2018 for her university. Since many years, 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). For her outreach activities she has been awarded with the Rainer-Markgraf-Preis 2020.
- CV (German) [PDF] [short text]
- Short CV (Englisch) [PDF]
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.
- Orcid
- see DBLP, Scholar, Semantic Scholar or the research information system of University of Bamberg FIS
- you can also find me at research gate and ACM DL
- until 2020: publication list generate by univis,
- My Erdös Number is 4
- Printable list by category [PDF]
- Selected talks
Selected Activities
Machine Learning Journal, Special Issue on Learning and Reasoning
Görz, Braun, Schmid, 2021, Handbuch für Künstliche Intelligenz, 6. Auflage
- For media coverage and other miscellaneous information see News
- For outreach talks about AI and machine learning see Talks
- Member of the Bavarian AI Council (Bayerischer KI-Rat)
- Board member of the Bavarian Institute of Digital Transformation (bidt)
- Head of the Fraunhofer IIS project group Comprehensible Artificial Intelligence (CAI)
- 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)
- Contact person for the AK KI in Schules (KiS) of the GI FBKI, see also AI & Education page
- Head of working group 1 -- Technologies and Data Science -- of Plattform Lernende Systeme (since 2022)
- Member of "Zentrum für vertrauenswürdige KI" (ZVKI)
- Steering Committee member of the International Joint Conference on Learning and Reasoning (IJCLR)
- Special Issue on Explainable and Interpretable Machine Learning and Data Mining in Data Mining and Knowledge Discovery (2021,2022)
- Chair of KI 2020
- Co-Organiser of the XI-ML Workshop at KI 2020
- Organizer of the seminar series Approaches and Applications of Inductive Programming (AAIP)
- AAIP @ IJCLR 2023
- AAIP 2023 as Dagstuhl Seminar 23442
- AAIP @ IJCLR 2022
- AAIP @ IJCLR 2021
- AAIP 2021 as Dagstuhl Seminar 21192
- AAIP 2019 as Dagstuhl Seminar 19202
- AAIP 2017 as Dagstuhl Seminar 17382
- AAIP 2015 as Dagstuhl Seminar 15442
- AAIP 2013 as Dagstuhl Seminar 13502
- AAIP 2011 at LOPSTR in Odense, Denmark
- AAIP 2009 at ICFP in Edinburgh, Scotland
- AAIP 2007 at ECML in Warsaw, Poland
- AAIP 2005 at ICML in Bonn, Germany
- Organizer of the First European Workshop on Cognitive Modeling (1996), now International Conference on Cognitive Modeling (ICCM)
- Member of the EU TAILOR network
- Board member of EPSRC funded Human-Like Computing Network+
- 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
- Head of the Elementary Computer Science Research Group (Computer Science for Kids, FELI), since 2015, see also Teaching AI to Kids and Non-experts (AI and Education)
- Initiation, organization and execution 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 speaker of the SIG Cognition of the Artificial Intelligence Section (FBKI, in German: GI-Fachbereich Künstliche Intelligenz) within the German Informatics Society (GI)
- 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.