Speculative Sampling For Faster Molecular Dynamics
Accepted at ICML 2026
PhD Student • TUM/Meta
I am a PhD student at the TUM Data Analytics and Machine Learning Group (advised by Stephan Günnemann), external research collaborator with the Meta FAIR chemistry team and theoretical physicist by training. I get excited by ML method development that solves tangible bottlenecks and is grounded in beautiful algorithmic ideas. This has led me to problems in molecular dynamics, graph machine learning and differential privacy.
Accepted at ICML 2026
ICLR 2026 Workshop on Geometry-grounded Representation Learning
Advances in Neural Information Processing Systems 37 (NeurIPS 2024)
Advances in Neural Information Processing Systems 37 (NeurIPS 2024)
Proceedings of the 40th International Conference on Machine Learning (ICML 2023)
Machine Learning and the Physical Sciences Workshop, NeurIPS 2023
* Equal contribution. † Shared corresponding author.