I am a PhD Candidate in Artificial Intelligence for Breast Cancer Research, under supervision of Kevin Groot-Lipman, Ritse Mann and Jonas Teuwen, as part of the AI for Oncology Lab at the Netherlands Cancer Institute. I am also part of the Breast Imaging Group at the Radboud University Medical Centre. In addition, I work together with the Columbia University Irving Medical Center .

My research focuses on developing large-scale vision foundation models for MRI, with an emphasis on learning robust, transferable representations from imaging data. By adapting these models to downstream clinical tasks, my work aims to improve personalization across the breast cancer care pathway.

Featured Publications

Preprint

Foundation Models in Medical Imaging: A Review and Outlook

Medical image analysis has traditionally relied on specialized solutions, each optimized for a particular modality, task, or dataset. While effective in controlled settings, these approaches struggle with the realities of clinical practice: …

Jun 1, 2025

Workshop Paper

Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders

Early detection of Barrett's Esophagus (BE), the only known precursor to Esophageal adenocarcinoma (EAC), is crucial for effectively preventing and treating esophageal cancer. In this work, we investigate the potential of geometric …

Jan 1, 2023

Thesis

Autotuning PID control using Actor-Critic Deep Reinforcement Learning

Precise control is essential for robotic manipulation in real-world environments, where actuator dynamics, load changes, and physical constraints prevent ideal tracking of control commands. Classical Proportional–Integral–Derivative (PID) …

Dec 1, 2020

Recent Publications

Veenboer, Tim, Yiasemis, George, Marcus, Eric, van Veldhuizen, Vivien, Snoek, Cees GM, Teuwen, Jonas, Lipman, Kevin BW (2025). TAP-CT: 3D Task-Agnostic Pretraining of Computed Tomography Foundation Models. arXiv preprint arXiv:2512.00872.

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van Veldhuizen, Vivien, Botha, Vanessa, Lu, Chunyao, Cesur, Melis Erdal, Lipman, Kevin Groot, Horlings, Hugo, Sanchez, Clarisa, Snoek, Cees, Mann, Ritse (2025). Foundation Models in Medical Imaging: A Review and Outlook. arXiv preprint arXiv:2506.09095.

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Balkenende, Luuk, Ferm, Jonatan, van Veldhuizen, Vivien, Brunekreef, Joren, Teuwen, Jonas (2025). Potential Time and Recall Benefits for Adaptive AI-Based Breast Cancer MRI Screening. Journal of Magnetic Resonance Imaging.

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van Veldhuizen, Vivien, Gullo, Roberto Lo, Roa, Tina, Kapetas, Panagiotis, Teuwen, Jonas, Pinker, Katja (2025). Application of machine learning to breast MR imaging. Magnetic Resonance in Medical Sciences.

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van Veldhuizen, Vivien, Vadgama, Sharvaree, de Boer, Onno, Meijer, Sybren (2023). Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders. Cancer Prevention Through Early Detection.

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