Logan Mathesen

Data Scientist, Statistician

Tempe, Arizona, United States
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Summary

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Senior
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Top School
Logan Mathesen is a data scientist and statistician with eight years of experience bridging academic research and high-volume manufacturing analytics, currently driving statistical strategy and automated analysis at Intel Foundry. A PhD candidate in Industrial Engineering at Arizona State University and NSF Graduate Research Fellow, he specializes in black-box optimization, statistical learning, and design of computer experiments, with publications in IEEE and Winter Simulation venues and a best-student-paper finalist distinction. He has translated theory into practice through internships and co-ops at Intel, Toyota, and ViaSat, developing anomaly detection, metrology validation, and optimizer pipelines that doubled fault-finding rates in automotive model testing. At Intel he leads experimental design and process-control systems used globally, authors internal analysis tools and curricula, and shaped statistical culture by delivering thousands of hours of training. Notably, his research produced a novel Conditional Non-Homogeneous Poisson Process model to characterize finite-time search performance, reflecting a strong blend of theoretical rigor and production impact.
code8 years of coding experience
job5 years of employment as a software developer
bookDoctor of Philosophy - PhD, Industrial Engineering, Doctor of Philosophy - PhD, Industrial Engineering at Arizona State University
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Github Skills (20)

optimization9
ray8
python8
reinforcement-learning8
parallel8
pytorch7
java7
machine-learning7
deep-learning7
hyperparameter-optimization6
tensorflow6
stochastic6
large-language-models6
scaling6
data-science6

Programming languages (1)

Python

Github contributions (4)

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Contributions:10 commits, 4 PRs, 8 pushes in 1 year 1 month
stochastic-optimizationsoaradaptiveoptimizationstochastic
Contributions:10 commits, 7 pushes, 1 branch in 1 year
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