I am a PhD student in Machine Learning at the Max Planck Institute for Intelligent Systems in Tübingen supervised by Bernhard Schölkopf. I am part of the IMPRS-IS graduate program and the interdisciplinary track of the ELLIS PhD program where I am co-supervised by Alessandra Buonanno.
My research focuses on developing and adopting state-of-the-art Machine Learning methods to fascinating physics problems ranging from gravitational waves 🌌 to particle physics ⚛️. During my PhD, I am working on simulation-based inference and neural posterior estimation for gravitational wave signals as a developer of the DINGO package.
You can find me on 🐙Github, 🎓Google Scholar, 💼 LinkedIn, 🦋 BlueSky, and 🐦Twitter.
➡️ Are you looking for a Master’s thesis topic at the intersection of ML and physics? Perfect, drop me an email explaining your background, qualifications, and interests.
News
- (September 2025) 🌊 I will give two talks at the MIAPbP workshop “Build big or build smart: Examining scale and domain knowledge in machine learning for fundamental physics”, stay tuned!
- (July 2025) 🐦 You want to know what ravens and gravitational waves have in common? Join my talk at the Soapbox Science Event Tübingen!
- (May 2025) ⚛ My paper “Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics” got accepted at Machine Learning: Science and Technology.
- (January 2025) 🎥 The recording from my ML4PS spotlight talk is online.
- (December 2024) ✈️ I am attending NeurIPS in Vancouver. Reach out if you want to chat!
- (November 2024) 🏆 My paper “Flow Annealed Importance Sampling Bootstrap meets Differentiable Particle Physics” got selected for a spotlight contributed talk at the NeurIPS workshop Machine Learning and the Physical Sciences 2024!
Flow matching for gravitational wave detection.
— Yann LeCun (@ylecun) June 22, 2024
From @bschoelkopf and collaborators at Max Planck. https://t.co/5L1FlBRG4j