Sage Hahn
Senior Software Engineer at DeepHealth
New York, New York, United States
Summary
👤
Senior🎓
Top SchoolSage Hahn is a Senior Software Engineer based in New York with eight years of experience bridging academic research and production ML systems. Holding a PhD in Complex Systems and Data Science from the University of Vermont, Sage has applied advanced time-series, network analysis, and neuroimaging methods to large-scale studies and shipped domain-specific tooling and visualization libraries. At DeepHealth they moved from software engineer to senior engineer, translating research-grade algorithms into clinical-focused software. Comfortable across the ML stack, Sage combines rigorous statistical modelling with practical engineering practices and a track record of contributing to open-source research software. Unusually for an industry engineer, they maintain an active publication record and a portfolio site showcasing reproducible projects that reflect both theoretical depth and production sensibility.
8 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Complex systems and Data Science, Doctor of Philosophy - PhD, Complex systems and Data Science at University of Vermont
Github Skills (25)
python10
data-science10
multi-site-imaging10
pandas10
machine-learning10
data-structure10
decoding10
ml10
neuroscience10
sklearn10
neuroimaging10
data-analysis10
brain-imaging9
normalization9
data-structures9
Programming languages (6)
Github contributions (5)
sahahn/ABCD_Ev_Search
May 2019 - Oct 2022
Contributions:84 pushes, 1 branch in 3 years 5 months
sahahn/BPt
Jun 2019 - Dec 2022
The Brain Predictability toolbox (BPt), is a python based Machine Learning library designed primarily for tabular and neuroimaging specific neuroimaging data but can easily be generalized further.
Contributions:18 releases, 1446 commits, 94 PRs in 3 years 6 months
machine-learningneuroimagingpythonbptbrain-predictability-toolbox
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