Erik J. Bekkers
Erik J. Bekkers works on geometric deep learning and medical image analysis. At Eindhoven, his doctorate developed geometric methods for retinal images, including vessel tracking and curvature analysis. His later work studies neural networks that use group structure and symmetry to improve representations. He received medical image analysis awards in 2018 and a Dutch Veni grant in 2019 for context-aware AI. In 2019, he planned to move into geometric machine learning at the University of Amsterdam.
- Now at
- University of Amsterdam
- Works
- 112
- Citations
- 1,685
- h-index
- 21
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
2013–2017
Geometry for retinal images
He studied at Eindhoven from 2013–2017. The thesis developed medical image analysis using geometry in the group SE(2), with applications to blood-vessel tracking, object recognition and curvature-based biomarkers.
-
2016–2018
Develop learning and analysis methods
He began a postdoctoral role in September 2016. Its tasks include geometric methods for tracking and segmenting vessels and neurons in two- and three-dimensional data. His work connects mathematical structure with medical image analysis.
-
2018
Recognition for medical image research
Bekkers received a MICCAI Young Scientist Award and a Philips Impact Award at Medical Imaging with Deep Learning in 2018.
-
2019
Context-aware AI and Amsterdam
In July 2019, he received a Veni grant for context-aware AI in medical images and an intended December start at Amsterdam. His research includes group convolutional networks, sparse representations and adaptive learning methods.
Sources and credits
Photo: ellis.eu; Erik J. Bekkers profile photograph; creator not stated. License: Not stated by source. Source: ellis.eu. Cropped to a square and resized. Ask us to remove or replace this photo.