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: – 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
Publications
- . . ‘SAM meets Gaze: Passive Eye Tracking for Prompt-based Instance Segmentation.’ Proceedings of Machine Learning Research 2023.
- . . ‘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.
- . . ‘EyeGuide - From Gaze Data to Instance Segmentation.’ Contributed to the The British Machine Vision Conference (BMVC), Aberdeen.
- . . ‘Cell Selection-based Data Reduction Pipeline for Whole Slide Image Analysis of Acute Myeloid Leukemia.’ In The IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), edited by , 1825–1834. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. doi: 10.1109/CVPRW56347.2022.00199.
Jacqueline Kockwelp
