I am a machine learning researcher at Qualcomm AI Research, Amsterdam. Previously I was a postdoc in Max Welling’s Philips group with the Amsterdam Machine Learning Lab (AMLAB) at the University of Amsterdam. I did my PhD at UCL in the Machine Vision Group with Gabriel J. Brostow and Dr. Clare Wilson FRCOphth. Before that I studied engineering at The University of Cambridge, and am a scholar of Sidney Sussex College.

My current research interests include equivariance and combinatorial optimization, while previously I have worked on uncertainty quantification, unsupervised representation learning, variational inference, normalizing flows, optimization, and medical imaging.

For the last two years I lectured a course in Bayesian Statistics for Machine Learning, and have been the lab manager for the Philips lab at the UvA. I am proud contributor to the UvA Inclusive AI Initiative, which seeks to promote diversity and inclusion in the academic AI world.

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Current Masters Students

Alessandra van Ree: Neural PDE Solvers

Previous Masters Students

Eli de Smet: Simple Saddle-Free Newton Descent with a Pseudo-Hessian
Jan Huiskes: FF-net: A fast Fourier transform inspired neural network
Rob Hesselink: Contrastive Learning of Equivariant Representations
Vivian van Oijen: Esophageal histopathology screening
Bryan Cardenas: Esophageal histopathology screening
Christina Winkler: Conditional Normalizing Flows
Nichita Diaconu: Learning convolutions
Jonas M J Braun: Non-geometric equivariance
Marios Fournarakis: Equivariance for tracking
Tycho van der Ouderaa: Reversible Networks for Memory-efficient Image-to-Image Translation in 3D Medical Imaging
Saki Shinoda: Semi-supervised learning