Jacob Bamberger
United Kingdom
Summary
👤
Senior🎓
Top SchoolJacob Bamberger is a research-driven machine learning engineer with eight years of experience bridging mathematics, topological data analysis, and geometric deep learning. Currently a Research Intern on Microsoft's Applied Sciences team working on diffusion LLMs, he brings a strong academic pedigree including a PhD in Computer Science from Oxford and research stints at EPFL and McGill. His work spans graph machine learning, higher-order information structures, and local homology tools—capabilities evidenced by publications and an ICML workshop paper. Equally comfortable in theory and applied settings, Jacob has repeatedly translated advanced mathematical ideas into practical ML research and tooling. Notably, his background in geometric group theory and topological methods gives him a distinctive lens for designing models that respect complex relational structure.
8 years of coding experience
3 years of employment as a software developer
Exchange student, Mathematics and Computer Science, Exchange student, Mathematics and Computer Science at University of California, BerkeleyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of OxfordMaster's degree, Computer Science, Master's degree, Computer Science at EPFL (École polytechnique fédérale de Lausanne)Master of Science - MSc Thesis, Geometric Group Theory, Master of Science - MSc Thesis, Geometric Group Theory at McGill University
French, English, Swedish
Github Skills (11)
topology10
topological-data-analysis10
localhost10
toolbox9
mapper9
machine-learning8
equivalence8
scikit-learn8
high-performance8
python7
factorization6
Programming languages (4)
Github contributions (5)
jacobbamberger/GraphCovers
Jun 2022 - Oct 2022
Code accompanying the paper "A Topological characterisation of Weisfeiler-Leman equivalence classes"
Contributions:36 commits, 3 PRs, 25 pushes in 4 months
topological-data-analysisequivalencefactorization
jacobbamberger/giotto-tda
Jul 2021 - Aug 2022
A high-performance topological machine learning toolbox in Python
Contributions:1 PR, 20 pushes, 4 branches in 1 year 1 month
pythontopological-machine-learningtoolboxmachine-learningtopology
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