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KogWis 2012 in Bamberg


ausführlich

Kolloquium 04.06.12, 16:00 Uhr

F. Wysotzki, TU Berlin: Lernen von Entscheidungsbäumen bei Trainingsobjekten mit objektabhängigen Kosten für Fehlentscheidungen
ausführlich

Vortrag Kinderuni

Wie lernen Computer und Roboter?
ausführlich

ITCO Absolventenpreis

Christophe Quignon erhält ITCO Absolventenpreis
ausführlich

27.10.11

Studentisches Projekt präsentiert Usability-Studie
ausführlich

Kolloquium 12.07.11, 10 Uhr

Mark Wernsdorfer: Grounding Affordances in Hierarchical Representations of Sensorimotor Interaction
ausführlich

Pain Face Day at 17.6.11


ausführlich

Kolloquium 14.07.11, 16 Uhr

Petra Hofstedt, Lehrstuhl für Programmiersprachen und Compilerbau, BTU Cottbus: Multi-paradigm Programming
ausführlich

News

Prof. Dr. Ute Schmid

 

Head of Cognitive Systems Group

Contact

Address:
Professur für Angewandte Informatik insb. Kognitive Systeme
Fakultät Wirtschaftsinformatik und Angewandte Informatik
Otto-Friedrich-Universität Bamberg
D-96045 Bamberg

Office: Room F 125
Feldkirchenstraße 21,  D-96052 Bamberg

Consultation Hour: by appointment

Phone: ++49-0951-863 2860

Fax: ++49-951-863 2862

E-Mail: Mail to Ute Schmid

CV

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 AI/Machine Learning group, Department of Computer Science, TUB. Afterwards she worked as lecturer (akademische Rätin) at the Department of Mathematics and Computer Science at University Osnabrück. Since 2004 she holds a professorship of Applied Computer Science/Cognitive Systems at the University of Bamberg. Her research interests are mainly in the domain of high-level learning on structural data, especially inductive programming, 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 and usability evaluation.

Research

Publications

Selected Activities 

Teaching