I am an associate professor at GRAPPA, the center of excellence for GRavitation AstroParticle Physics Amsterdam, and the Institute of Physics at the
University of Amsterdam. Currently, I lead as Principle Investigator the ERC consolidator
project UnDark. I use Machine Learning to shed light on the mysteries of the
dark Universe.
We aim at finding signals of physics beyond the Standard Model using a wide range of astrophysical observations. Our ultimate goal is to shed light on dark matter and other mysteries of the dark Universe. We focus on new observational approaches and technical challenges that others have not been able to overcome. An important component is to train the next generation of astroparticle physicists in cutting-edge machine learning techniques.
For information about possible Bachelor and Master projects in my group checkout out the GRAPPA website, or contact me directly.
Research projects, research initiatives & experimental collaborations
Principal Investigator. We explore new approaches to uncover dark matter in the post-WIMP era.
Principal Investigator. With Sascha Caron (Radboud), the eScience center and SURFsara we use probabilistic differentiable programming to improve and to steer physical simulators for particle collisions (ATLAS/LHC) and for strong lensing images.
Group leader. We use AI for better modeling and searches of gravitational wave signals with the LIGO/Virgo detectors.
Co-Investigator. The Hidden Universe of Weakly Interacting Particles. We will investigate the properties of the most elusive particles in our universe – neutrinos and dark matter.
Member of the CTA consortium. We are interested in searching for gamma-rays from dark matter and studying primordial magnetic fields.
Co-organizer. Dark Machines is a research collective of physicists and data scientists with the goal to uncover the mysteries of the dark Universe.
Former lead of DarkBit, core development. We perform the global analyes of beyond-the-standard model physics.
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For a full list of publications see inspirehep.net
