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
- Beckmann, Daniel, Kockwelp, Jacqueline, Gromoll, Joerg, Kiefer, Friedemann, and Risse, Benjamin. . “SAM meets Gaze: Passive Eye Tracking for Prompt-based Instance Segmentation.” Proceedings of Machine Learning Research, № 2023
- Kockwelp, Jacqueline, Thiele, Sebastian, Bartsch, Jannis, Haalck, Lars, Gromoll, Jörg, Schlatt, Stefan, Exeler, Rita, Bleckmann, Annalen, Lenz, Georg, Wolf, Sebastian, Steffen, Björn, Berdel, Wolfgang Eduard, Schliemann, Christoph, Risse, Benjamin, and Angenendt, Linus. . “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.
- Kockwelp, Jacqueline, Gromoll, Jörg, Wistuba, Joachim, and Risse, Benjamin. . “EyeGuide - From Gaze Data to Instance Segmentation.” contribution to the The British Machine Vision Conference (BMVC), Aberdeen
- Kockwelp, Jacqueline, Thiele, Sebastian, Kockwelp, Pascal, Bartsch, Jannis, Schliemann, Christoph, Angenendt, Linus, and Risse, Benjamin. . “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), In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, edited by IEEE/CVF. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. doi: 10.1109/CVPRW56347.2022.00199.
Jacqueline Kockwelp
