Fernando Cervantes-sánchez
Systems Analyst at The Jackson Laboratory
Bar Harbor, Maine, United States
Summary
👤
Senior🎓
Top SchoolFernando Cervantes-sánchez is a Systems Analyst with a PhD in Computer Science and a decade of experience applying computational intelligence to medical image analysis. Based at The Jackson Laboratory in Bar Harbor, he bridges research and applied development, integrating AI methods into decision-support tools for clinical practice. His background includes developing deep learning models and neural architecture search techniques at CIMAT, paired with an engineering foundation in quality and process improvement from industry roles at Nissan. Fernando combines rigorous academic training with practical systems thinking and Lean Six Sigma sensibilities, enabling reproducible, production-ready imaging solutions. He is comfortable moving projects from experimental models to institution-scale IT environments, bringing both statistical engineering and hands-on implementation experience.
10 years of coding experience
1 year of employment as a software developer
PhD, Computer Science, PhD, Computer Science at Centro de Investigación en Matemáticas, A.C.BE, Statistical Industrial Engineer, BE, Statistical Industrial Engineer at Universidad Autónoma de AguascalientesMSc, Computer Science, MSc, Computer Science at Centro de Investigación en Matemáticas, A. C.Yellow Belt, Lean Manufacturing, Yellow Belt, Lean Manufacturing at Lean Six Sigma Institute
English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (24)
python10
image-processing10
image10
geometric10
computer-vision10
geometry8
manipulation7
zarr5
pluto5
sympy4
binder4
data-wrangling4
stable4
segmentation4
classification3
Programming languages (6)
Github contributions (5)
TheJacksonLaboratory/zarrdataset
Apr 2023 - Apr 2025
A dataset for loading zarr files to be used in machine learning training pipelines
Contributions:3 releases, 1 review, 11 PRs in 1 year 11 months
imaging-solutions
TheJacksonLaboratory/activelearning
Apr 2024 - Mar 2025
Active learning tools for fine-tuning ML models
Contributions:12 releases, 47 PRs, 109 pushes in 11 months
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