Anton Baumann is a research-focused machine learning engineer and Master's student at TUM currently writing his thesis at ETH Zürich, with eight years of hands-on experience spanning probabilistic ML, vision-language models, and geospatial earth-observation applications. He has contributed to high-profile venues (NeurIPS workshops, ICCVW) and built practical systems from geometric deep learning for molecular property prediction to a provisional-patent-backed optical-flow extension for curved surfaces. His work blends rigorous probabilistic modeling and applied engineering—implementing uncertainty-aware pixel-wise regression for satellite imagery and production-ready tooling in Go for ad-tech. Selected competitively for research roles (1 of 69 from 4,300 applicants), Anton thrives at the intersection of research and production, often turning theoretical ideas into reproducible code and peer-reviewed publications.
8 years of coding experience
4 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at KTH Royal Institute of Technology
Bachelor of Science - BS Computer Science and Mathematics, Bachelor of Science - BS Computer Science and Mathematics at Technical University of Munich
Abitur, Abitur at Humanistisches Wilhelmsgymnasium München
Contributions:4 releases, 7 reviews, 49 commits in 8 months
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Anton Baumann - Research Assistant at Aalto University