Research Foci
- Machine / Deep Learning für Image Processing
- Biomedizinische Bildgebung
- Neuartige Annotationsmethoden für Daten
CV
Academic Education
- Ph.D. studies, Computer Vision & Machine Learning Systems group (Prof. Benjamin Risse)
- Master of Science (Computer Science), University of Münster
- Bachelor of Science (Computer Science), University of Münster
Honors
- Paper of the Month – Medizinische Fakultät der Universität Münster
- Nominated for: Women Informatics Thesis Award – Gesellschaft für Informatik e.V. (GI)
- Förderpreis der Angewandten Informatik (1st prize) – IHK Nord Westfalen
- REACH Thesis Award (Bachelor & Master Thesis) (1st prize) – REACH - EUREGIO Start-up Center
Articles
- Thiele, S., Kockwelp, J., Wistuba, J., Kliesch, S., Gromoll, J., & Risse, B. (). Investigating Imaging, Annotation and Self-Supervision for the Classification of Continuously Developing Cells in Histological Whole Slide Images. IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, Arizona.
- Kockwelp, J., Beckmann, D., & Risse, B. (). Human Gaze Improves Vision Transformers by Token Masking. Gaze Meets Computer Vision @ Winter Conference on Applications of Computer Vision (WACV) Workshops , Tucson, Arizona.
- Ernsting, J., Beeken, PN., Ogoniak, L., Kockwelp, J., Roll, W., Hahn, T., Busch, AS., & Risse, B. (). Towards population scale testis volume segmentation in DIXON MRI. Computers in Biology and Medicine, 198, 111139–111139. doi: 10.1016/j.compbiomed.2025.111139.
- Kockwelp, J., Kliesch, S., Gromoll, J., Wistuba, J., & Risse, B. (). MARTHA - Combining gaze into deep learning for fully quantitative human testicular histology analysis. Computers in Biology and Medicine, 199, 111270. doi: 10.1016/j.compbiomed.2025.111270.
- P, B., J, E., L, O., J, K., T, H., B, R., & Busch, A. S. (). Unveiling the genetic architecture of testicular volume: a population-based GWAS using machine learning-based mri segmentations. in Hokken-Koelega, A., & Bertherat, J. (ed.), Endocrine AbstractsJoint Congress of the European Society for Paediatric Endocrinology (ESPE) and the European Society of Endocrinology (ESE) 2025: Connecting Endocrinology Across the Life Course (p. 993–993). BiosciAbstracts. doi: 10.1530/endoabs.110.P993.
- Kockwelp, J., Thiele, S., Bartsch, J., Haalck, L., Gromoll, J., Schlatt, S., Exeler, R., Bleckmann, A., Lenz, G., Wolf, S., Steffen, B., Berdel, W. E., Schliemann, C., Risse, B., & Angenendt, L. (). Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears. Blood Advances, 8 (1), 70–79. doi: 10.1182/bloodadvances.2023011076.
- Beckmann, D., Kockwelp, J., Gromoll, J., Kiefer, F., & Risse, B. (). SAM meets Gaze: Passive Eye Tracking for Prompt-based Instance Segmentation. Proceedings of Machine Learning Research, 2023.
- Kockwelp, J., Gromoll, J., Wistuba, J., & Risse, B. (). EyeGuide - From Gaze Data to Instance Segmentation. The British Machine Vision Conference (BMVC), Aberdeen.
- Kockwelp, J., Thiele, S., Kockwelp, P., Bartsch, J., Schliemann, C., Angenendt, L., & Risse, B. (). Cell Selection-based Data Reduction Pipeline for Whole Slide Image Analysis of Acute Myeloid Leukemia. in IEEE/CVF (ed.), In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern RecognitionThe IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) (pp. 1825–1834). doi: 10.1109/CVPRW56347.2022.00199.
Jacqueline Kockwelp
