Karol Gotkowski

Machine Learning Engineer

Karol Gotkowski is a machine learning engineer in the Applied Computer Vision Lab (ACVL) at the Deutsche Krebsforschungszentrum in Heidelberg.

The focus of his work is to develop pragmatic data-driven deep learning solutions together with collaboration partners from all over Helmholtz and beyond to expand the use of AI in a multitude of different domains. These collaborations range from diabetes detection in whole slide images, to mineral particle instance segmentation for automated mineral quantification, to bubble detachment analysis during the process of electrolysis.

Karol has a M.Sc. degree in computer science from the Technische Universität Darmstadt.


Gotkowski, K., Gupta, S., Godinho, J. R. A., Tochtrop, C. G. S., Maier-Hein, K. H., & Isensee, F. (2024). ParticleSeg3D: A scalable out-of-the-box deep learning segmentation solution for individual particle characterization from micro CT images in mineral processing and recycling. Powder Technology, 434, 119286. https://doi.org/10.1016/j.powtec.2023.119286
Gotkowski, K., Gonzalez, C., Kaltenborn, I. J., Fischbach, R., Bucher, A., & Mukhopadhyay, A. (2022, June 22). i3Deep: Efficient 3D interactive segmentation with the nnU-Net. Medical Imaging with Deep Learning. https://openreview.net/forum?id=R420Pr5vUj3