I am a PhD student in machine learning under supervision of Max Welling at the QUVA lab of the University of Amsterdam, as well as a Research Associate at Qualcomm AI Research. Currently I am working on the intersection of data-efficient machine learning and geometry.
Previously, I was a masters student Artificial Intelligence in Amsterdam, where I worked on geometric auto-encoders and variational inference. I wrote my thesis on Causal Imitation Learning as visting scholar at the Robotic AI and Learning Lab at UC Berkeley supervised by Sergey Levine.
Before moving to AI, I studied the inner working of the universe with a masters in theoretical physics at the University of Cambridge and a bachelors in physics from the University of Amsterdam.
Have a look at my Resume.
I am currently interested in the applications and theory of geometric deep learning, which can allow for data-efficient learning on signals on spaces that are not flat 2D space. In addition, I think causality is quite interesting.