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, 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
- (January 2025) 🎥 The recording from my ML4PS spotlight talk is online (I don’t dare to watch it, but other people might be interested).
- (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!
- (October 2024) 🔭 New paper alert: “Flow Matching for Atmospheric Retrieval of Exoplanets: Where Reliability meets Adaptive Noise Levels” lead by Timmy
- (October 2024) 🏆 I received a WiML NeurIPS travel award for the best poster at the 2nd Tübingen Women in ML workshop
- (September 2024) 🌊 I gave a lecture and tutorial on normalizing flows at the ODSL GenAI Workshop in Munich.
- (June 2024) 💻 Interested in a introduction to DINGO? Here’s a Colab notebook to start with.
Flow matching for gravitational wave detection.
— Yann LeCun (@ylecun) June 22, 2024
From @bschoelkopf and collaborators at Max Planck. https://t.co/5L1FlBRG4j