Are you looking for a degree programme that doesn’t just teach theory from books, but puts the knowledge you’ve learnt directly into practice through laboratory tests, demonstration experiments and project work?
The Institute of Computer Science (IFI) supports you during your studies at the Faculty of Computer Science (I) by providing an ideal environment. For a practice-oriented Bachelor’s or Master’s degree or a dual study programme. We bridge the gap between academic excellence and direct application in state-of-the-art laboratories. Our staff at the IFI are also happy to support you should you have any questions.
Our professors and staff are organized into seven subject areas. In this way, we cover a broad spectrum of basic and application-oriented areas in computer science:
The goal of this research project is to offer people with periodic limb movements during sleep (PLMS) the opportunity to monitor their therapy at home according to their needs and to provide them with recommendations for action. By using readily available sensors in combination with AI-based analysis of the collected data, the goal is to create a system that meets the requirements of a medical device while making the high complexity of the necessary measurement data manageable.
Detailed information about the project is available at: RLS Therapy Assistant
Contact person: Prof. Dr. Neltje Piro
The Service Robotics Research Group at Ulm University of Applied Sciences focuses on methods, algorithms, and software tools for developing service robots for everyday use. The focus here is on applied research and development. The approaches are evaluated using real robots in everyday environments. Areas of application include Industry 4.0 scenarios, intralogistics scenarios, agricultural scenarios, and household robots.
Research activities are conducted in cooperation and collaboration with industry, skilled trades, SMEs, and large-scale industry at the regional, national, and international levels within the framework of public funding programs, joint research programs, and contract research.
Detailed information about the research group and the individual projects is available at: Service Robotics
Contact: Prof. Dr. Christian Schlegel
The AI for Sensor Data Analytics research group is based within the Biomechatronics Laboratory at the Institute of Medical Technology and Mechatronics—a multidisciplinary laboratory that comprises several research groups with shared areas of application.
The AI for Sensor Data Analytics research group conducts research in the field of artificial intelligence with a focus on machine learning and deep learning for sensor data analysis.
For detailed information about the project, please visit: www.aisd-ulm.de
Contact: Prof. Dr. Michael Munz
Prof. Dr. Klaus Baer (Software Engineering)
Prof. Dr. Michel Börner (Artificial Intelligence)
Prof. Dr. Benedikt Eberhardinger (Cloud Engineering & Computing)
Prof. Dr. Alfred Michael Franz (Medical Informatics)
Prof. Dr. Markus Goldstein (Artificial Intelligence, Data Science)
Prof. Dr. Philipp Graf (Software Engineering)
Prof. Dr. Thorsten Hasbargen (Software Engineering)
Prof. Dr. Volker Herbort (Data Science)
Prof. Dr. Joachim Hering (Software Engineering)
Prof. Dr. Karin Lunde (Data Science)
Prof. Dr. Rüdiger Lunde (Software Engineering, Artificial Intelligence)
Prof. Dr. Michael Munz (Artificial Intelligence)
Prof. Dr. Tim Pietzcker (Medical Informatics)
Prof. Dr. Neltje Piro (Medical Informatics)
Prof. Dr. Markus Schäffter (Secure Systems)
Prof. Dr. Georg Schied (Software Engineering)
Prof. Dr. Christian Schlegel (Artificial Intelligence, Technical Informatics, Secure Systems)
Prof. Dr. Marianne von Schwerin (Artificial Intelligence)
Prof. Dr. Reinhold von Schwerin (Artificial Intelligence, Data Science)
Prof. Dr. Frank Steiper (Computer Engineering)
Prof. Dr. Manfred Strahnen (Computer Engineering)
Prof. Dr. Kathrin Stucke-Straub (Data Science)
Prof. Dr. Stefan Traub (Cloud Engineering & Computing, Secure Systems)
Prof. Dr. Bernd Vögel (Medical Informatics)
Prof. Dr. Ursula Weiß (Software Engineering)
Prof. Dr. Manfred Wilhelm (Data Science)
