Biography
Dr. Jens Rittscher was appointed as a Senior Research Fellow in 2013 and he is the first joint academic appointment between the Institute of Biomedical Engineering and the Nuffield Department of Medicine. He was elected a Professor of Engineering Science in 2014 and is now an adjunct member of the Ludwig Institute of Cancer Research and the Wellcome Centre for Human Genomics. Since 2018 he is a group leader in the Oxford Big Data Institute where his research group is now based.
Before coming to Oxford in 2013, Jens led the Computer Vision Laboratory at GE Global Research in Niskayuna, NY, USA. He joined GE in 2001 after completing his DPhil at Oxford. During his doctoral studies at Oxford, he was part of the Visual Dynamics Group led by Andrew Blake as a Marie Curie Fellow funded by the EU. He received his Diploma in Mathematics and Computer Science from the University of Bonn, Germany.
His research interests lie in enabling biomedical imaging through the development of new analysis algorithms and novel computational platforms, with a current focus to improve mechanistic understanding of cancer and patient care through quantitative analysis of image data. In addition to his research in the field of biomedical imaging, Jens has worked extensively in the area of video surveillance, the automatic annotation of video, and the understanding of volumetric seismic data. He co-founded Ground Truth Labs Ltd to commercialise research in computational pathology from his laboratory in 2019.
Previously, Jens held a position as an adjunct assistant professor at the Rensselaer Polytechnic Institute, Troy, NY, USA. From 2018 to 2020 Jens was chair of the IEEE ISBI Steering Committee. At present, he is a co-director for the EPSRC Centre for Doctoral Training in Health Data Science. Since 2021 he is a member of the UK EPSRC Healthcare Technologies Strategic Advisory Team.
Publications
View a list of Professor Rittscher's publications on Google Scholar, or by using his ORCID ID.
Research Interests
The aim of Jens' research is to enhance our understanding of complex biological processes through the analysis of image data that has been acquired at the microscopic scale. Jens develops algorithms and methods that enable the quantification of a broad range of phenotypical alterations, the precise localization of signalling events, and the ability to correlate such events in the context of the biological specimen. This work can be structured into the following three major areas:
- Analysis of shape, structure, and spatial context,
- Function and dynamic biological processes,
- Enablement of new imaging methods.
This algorithm development needs to be guided by a firm understanding of the broader application context which is indicated in the figure below. Sophisticated algorithms are now necessary to image increasingly complex model systems over an extended period of time. In order to understand the role of certain genetic modifiers we need to relate these to the image derived measurements and features.
