Andrew Berger
Post-bacc at Stanford University
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolAndrew Berger is an applied machine learning practitioner based in the San Francisco Bay Area with 12 years of technical experience spanning academia, startups, and industry. After a BA in Mathematics and Physics from UC Berkeley, he has worked on deep learning for drug discovery, contributed to medical imaging tooling (notably backend improvements to the ANTsPy library), and is currently a post-bacc researcher in a biology lab at Stanford. He combines hands-on code-level contributions—file I/O, validation, and robustness fixes in open-source imaging software—with experience leading early-stage product and engineering efforts as a startup co-founder. Available for ML consulting, he brings a mix of experimental research rigor and practical engineering pragmatism, plus a knack for finding and fixing subtle edge-case bugs that surface in real data.
12 years of coding experience
3 years of employment as a software developer
Bachelor of Arts (B.A.), Mathematics, Physics, Bachelor of Arts (B.A.), Mathematics, Physics at University of California, Berkeley
English
Stackoverflow
121reputation
14kreached
2answers
2questions
Github Skills (19)
python10
medical-imaging10
lib9
numpy9
data-handling9
file-processing8
file-handling8
file-access8
fileio8
debugging7
refactor7
refactoring7
mongodb6
memory-management6
sparse-matrix6
Programming languages (8)
Github contributions (5)
ANTsX/ANTsPy
Feb 2020 - Feb 2022
A fast medical imaging analysis library in Python with algorithms for registration, segmentation, and more.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:7 commits, 7 PRs, 42 comments in 2 years
Contributions summary:Andrew primarily focused on improving the `antspy` library's functionality and robustness, specifically related to medical imaging analysis. Their contributions involved adding input validation to the `plot` function to handle edge cases and prevent errors, and modifying code to improve data handling. They also merged in updates from the `master` branch and fixed an issue related to dimension inference, which includes updates to file parsing. The user demonstrated an understanding of the library's codebase and data structures, including file I/O.
imagingpythonsegmentationmedical-imagingneuroimaging
andbberger/spin-glass
Dec 2013 - Feb 2014
Contributions:24 commits in 1 month
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