AI for Astrophysics

I am a Research Assistant in the Astroparticle Physics Lab and the Gravitational Astrophysics Lab at NASA Goddard Space Flight Center. I have an MSc. in Computer Science from KU Leuven and research experience in applying AI to astrophysics in numerous projects at NASA and ESA.

Research interests

My current research interests involve solving interesting inverse problems in (astro)physics. Coming from a computer science background, I see a huge potential for AI methods to be applied to these problems. Traditional (non-AI) methods are often too inefficient, cannot handle large datasets or suffer from analytic degeneracies. With the incoming wave of data from the current and future astronomical campaigns, astrophysics needs new methodologies.

Current and past projects

At ESA's Advanced Concepts Team, I reconstructed the Dark Matter distribution in the Galactic Center using orbits of the closest stars [arXiv:2308.09170].
As part of an Honour's project at KU Leuven, I constructed a neural network to spectral functions (and complex poles) of confined particles in high energy physics [SciPostPhys.13.4.097].
At NASA Goddard Space Flight Center, I am currently doing research on neutron stars. In particular, we are inferencing neutron star parameters from NICER and Fermi data using neural networks.