Scott Trinkle
Research Senior Scientist, Machine Learning at Waters Corporation
Atlanta, Georgia, United States
Summary
👤
Senior🎓
Top SchoolScott Trinkle is a Research Senior Scientist in Machine Learning at Waters Corporation with eight years of experience building data-driven tools for mass spectrometry, liquid chromatography, and medical imaging. He holds a PhD in Medical Physics from the University of Chicago, where his thesis combined multi-modal, multi-scale validation of MRI microstructure with graph-theory analyses and NIH-funded research. Scott bridges research and production: he designs interactive visualization and diagnostics pipelines, registers heterogeneous 10 MB–10 TB imaging datasets, and ships robust data-processing software. His open-source QA work on the widely used DIPY medical-imaging library highlights a commitment to test-driven reliability in scientific code. Based in Atlanta, he blends deep domain expertise in neuroimaging with practical ML and engineering skills to translate complex imaging science into production-ready tools. An unexpected strength is his track record of exposing geometric bias in tractography, showing he not only builds systems but also uncovers hidden assumptions in imaging-derived networks.
8 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD, Medical Physics, Doctor of Philosophy - PhD, Medical Physics at The University of ChicagoBachelor of Science - BS, Nuclear and Radiological Science, Summa Cum Laude, Bachelor of Science - BS, Nuclear and Radiological Science, Summa Cum Laude at University of Florida
Github Skills (9)
testing10
medical-imaging10
python10
diffusion-mri9
numpy8
pytest7
machine-learning6
trac4
tractography4
Programming languages (4)
Github contributions (5)
dipy/dipy
Mar 2019 - Jul 2019
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:7 commits, 2 PRs, 7 comments in 4 months
Contributions summary:Scott primarily focused on adding tests and modifying existing tests to the dipy repository. Their contributions include adding a test for the `min_signal` default in Qball models, testing for the CSD convergence keyword, and asserting the results before/after applying the `convergence` keyword. These changes indicate a focus on verifying the accuracy and stability of the existing code by adding tests, modifying parameters, and comparing existing outcomes.
signalpythonmicrostructurespatialtractography
scott-trinkle/uCTdMRI
Feb 2018 - Jan 2020
Contributions:89 pushes, 7 branches in 1 year 11 months
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