Prof. Dr. Benjamin Risse
Interdisciplinary Machine Learning and Computer Vision Research
Mathematics / Mathematical Modelling / Image Analysis
We are interested in interdisciplinary research questions involving the development of novel imaging, computer vision and machine learning technologies yielding new approaches to acquire and analyse data with applications in medicine, biology and ecology. This requires a fundamental investigation of how computers perceive and understand complex real-world situations. By examining the entire process from data acquisition (i.e. sensing hardware) to quantitative evaluation (i.e. algorithms) we are seeking for solutions beyond classical image processing, pattern recognition and artificial intelligence methodologies. Many lessons remain to be learned to tackle the challenges of real-world data which we seek to study and reveal in the coming years to enable and build novel data-driven systems.
- 2005 - 2010: Diploma degree in computer science with a minor in biology , University of Münster
- 2011 - 2015: Ph.D. studies in Computer Science (Prof. Jiang) and Neurobiology (Prof. Klämbt), University of Münster
- 2012: Visiting Researcher at Sichuan University, China
- 2015 – 2017: PostDoc at the School of Informatics (Prof. Webb), University of Edinburgh
- 2017 – 2018: PostDoc at the University of Münster (Prof. Jiang), University of Münster
- Since 2018: W1 Professor at the University of Münster (Computer Vision and Machine Learning Systems Group)
Risse, B., Thomas, S., Otto, N., Löpmeier, T., Valkov, D., Jiang, X. and Klämbt, C., (2013). FIM, a novel FTIR-based imaging method for high throughput locomotion analysis. PloS one, 8(1).
Otto, N., Risse, B., Berh, D., Bittern, J., Jiang, X. and Klämbt, C., (2016). Interactions among Drosophila larvae before and during collision. Scientific reports, 6(1), pp.1-11.
Risse, B., Mangan, M., Del Pero, L. and Webb, B., (2017). Visual tracking of small animals in cluttered natural environments using a freely moving camera. In Proceedings of the IEEE International Conference on Computer Vision Workshops (pp. 2840-2849).
Otto, N., Marelja, Z., Schoofs, A., Kranenburg, H., Bittern, J., Yildirim, K., Berh, D., Bethke, M., Thomas, S., Rode, S. and Risse, B.,(2018). The sulfite oxidase Shopper controls neuronal activity by regulating glutamate homeostasis in Drosophila ensheathing glia. Nature communications, 9(1), pp.1-12.
Haalck, L., Mangan, M., Webb, B. and Risse, B., (2020). Towards image-based animal tracking in natural environments using a freely moving camera. Journal of neuroscience methods, 330, p.108455.