Christoph Hofer
Chief Solutions Architect at Metaroom by Amrax®
Klagenfurt-Villach Area Austria
Summary
👤
Senior🎓
Top SchoolChristoph Hofer is a Chief Solutions Architect and deep learning specialist with a PhD in Computer Science from Universität Salzburg and nine years of experience bridging industry-grade engineering and academic research. He combines production software experience from COPA-DATA with postdoctoral research on topological data analysis, publishing at ICML, NeurIPS and JMLR on the interplay between persistent homology and deep learning. Currently shaping solutions at Metaroom by Amrax® and AMRAX, he translates advanced ML research into practical architectures for real-world applications. Regularly serving as a reviewer for major machine learning conferences, he keeps close to cutting-edge methods while focusing on deployable systems. Based in the Klagenfurt-Villach area, he brings a rare mix of rigorous mathematical training and hands-on product engineering. Notably, his work emphasizes the symbiotic use of topology to make deep models more interpretable and structurally robust.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, 1, Doctor of Philosophy - PhD, Computer Science, 1 at Universität Salzburg
Github Skills (22)
python10
barcodes10
bar-code10
machine-learning10
essence10
topological-data-analysis10
deep-learning10
gpu10
reusability10
pytorch9
numpy9
autograd9
neural-network9
persistent9
tensor9
Programming languages (3)
Github contributions (5)
c-hofer/jmlr_2019
Jan 2018 - Mar 2020
Code for JMLR paper ``Learning Representations of Persistence Barcodes``
Contributions:94 commits, 2 PRs, 54 pushes in 2 years 2 months
bar-codebarcodes
c-hofer/tda-toolkit
Jun 2017 - Mar 2020
My persistent homology related code.
Contributions:46 commits, 2 PRs, 27 pushes in 2 years 9 months
persistent-homologyhomologypersistent
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