I am a PhD student in the group of Gregor Kasieczka at the University of Hamburg working at the intersection of machine learning and particle physics.
My current research focuses on building foundation models for particle physics applications.
During my bachelors and masters studies at the University of Freiburg I was working within the ATLAS collaboration at CERN, primarily in the field of flavor tagging. At the University of Bordeaux I was working with the group of Brahim Lounis in the field of nanophotonics. I also worked for some time in the Big Data analytics team at Bosch Sensortec, where I focused on automating data pipelines.
I’m interested in machine learning in general and its applications in particle physics. Furthermore, I’m passionate about stuff like CI/CD and containerization.
Education
- PhD in Physics, University of Hamburg (Since 2023)
- M.Sc. in Physics, University of Freiburg (2019 - 2022)
- ERASMUS semester, University of Bordeaux (2020 - 2021)
- B.Sc. in Physics, University of Freiburg (2016 - 2019)
Publications
- OmniJet-\(\,\alpha_C\): Learning point cloud calorimeter simulations using generative transformers - arXiv, GitHub
- Aspen Open Jets: Unlocking LHC Data for Foundation Models in Particle Physics - arXiv, GitHub
- Umami: A Python toolkit for jet flavour tagging - Journal, GitHub
- OmniJet-\(\,\alpha\): The first cross-task foundation model for particle physics - arXiv, Journal, GitHub
- Flow Matching Beyond Kinematics: Generating Jets with Particle-ID and Trajectory Displacement Information - arXiv, Journal ,GitHub
- High-resolution optical imaging of single magnetic flux quanta with a solid immersion lens - Journal