Ulm University

University of Ulm

As a young research university, Ulm University focuses its efforts on global challenges with 12 strategic and interdisciplinary research areas dedicated to the overarching themes of ageing, sustainability, future technologies as well as human health and well-being. Substantial third-party funding and numerous large collaborative projects such as Collaborative Research Centres as well as a Cluster of Excellence are a testimony to the University's research strength.

Ulm University was founded in 1967 as a higher education institution for medicine and natural sciences. Today, more than 10,000 students are receiving their education at the four faculties of 'Medicine', 'Natural Sciences', 'Mathematics and Economics' and 'Engineering Sciences, Computer Science and Psychology'. Over 60 study programmes, including an increasing number of English-taught courses, offer excellent career prospects. The University and its students also benefit from an outstanding international and regional network.

Ulm University is the centre of and driving force behind the Science City of Ulm with non-university research institutions, maximum-care hospitals and technology companies. The location in the heart of an economically strong region offers ideal conditions for the transfer of technology and knowledge.

LEXIS (Learning, Expert and Intelligent Systems) group is part of the Institute of Measurement, Control and Microtechnology at Ulm University. The group works in the field of machine learning and particularly deep learning with real-world applications on autonomous systems, computer vision, and medical image analysis. The current research activities are focused on learning in simulation, meta-learning, adversarial learning, multi-modal learning, information fusion, efficient inference and sequential modelling. A few examples of applied research include microscopy image segmentation, human pose estimation, activity recognition, forecasting, as well as self-localization, detection, tracking and trajectory prediction for self-driving cars.