Alexander Partin
Senior Computational Scientist
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolAlexander Partin is a Senior Computational Scientist with nine years of experience applying data science, deep learning, and advanced signal and image processing to medical and imaging problems. Based at Argonne National Laboratory, he progressed from software engineer to senior scientist leading research in the Data Science and Learning Division, translating academic rigor from his Ph.D. into production-ready algorithms. His background spans industry-grade imaging at Dolby (HDR and wide-gamut color systems with patent work) and hands-on medical ultrasound research, giving him a rare combination of perceptual color science and biomedical signal expertise. He routinely moves ideas from experimental setups and statistical analysis into deployable software (Python, C++, Matlab), and has a track record of inventing practical methods for matching nonlinear components in complex imaging chains. Known for bridging theoretical research and engineering delivery, he brings technical depth in imaging physics coupled with a pragmatic focus on reproducible, high-impact solutions.
9 years of coding experience
12 years of employment as a software developer
Bachelor’s Degree Electrical and Electronics Engineering, Bachelor’s Degree Electrical and Electronics Engineering at Braude Academic CollegeDoctor of Philosophy (Ph.D.) Electrical and Computer Engineering, Doctor of Philosophy (Ph.D.) Electrical and Computer Engineering at University of Rochester
English, Russian, Hebrew
Github Skills (11)
data-normalization7
feature-extraction6
benchmark4
machine-learning4
feature-engineering4
deep-learning3
ipython3
singularity3
transformer1
pytorch1
neural-network1
Programming languages (6)
Github contributions (5)
JDACS4C-IMPROVE/GraphDRP
Mar 2022 - May 2025
Contributions:1 review, 10 PRs, 170 pushes in 3 years 2 months
single-drp
DOE-NCI-Pilot1/Normalization
Aug 2019 - Jul 2020
Data Normalization
Contributions:15 commits, 20 pushes in 11 months
data-normalization
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