Noah Paulson
Computational Scientist
Chicago, Illinois, United States
Summary
👤
Senior🎓
Top SchoolNoah Paulson is a computational scientist at Argonne National Laboratory with over a decade of experience applying data-driven and Bayesian methods to materials science and thermodynamics. He has led multidisciplinary teams and secured significant funding (lead PI for $740K and co-PI on $2M) to develop open-source tools such as a Phase Diagram Uncertainty Quantification Python package and predictive workflows for battery lifetime and Ti microstructure performance. His work blends rigorous PhD-level modeling with practical software development, delivering orders-of-magnitude speedups in predictive workflows and reduced-order models for additive manufacturing. Based in Chicago, he bridges experimental and computational efforts, having designed combined experimental-computational studies and scalable Python pipelines. Notably, he couples uncertainty quantification and extrapolative functional-form choices to make thermodynamic predictions robust across extreme temperatures.
12 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Mechanical Engineering, 4.00/4.00, Doctor of Philosophy (Ph.D.), Mechanical Engineering, 4.00/4.00 at Georgia Institute of TechnologyB.S., Mechanical Engineering, B.S., Mechanical Engineering at Tufts UniversityUniversity of Auckland
English
Github Skills (47)
monte-carlo9
uncertainty8
python8
bayesian8
calibration8
materials-informatics8
sampling8
simulation8
modeling-tool7
algorithms7
scipy7
pythonic7
power-systems7
pbs7
distributed-computing7
Programming languages (2)
Github contributions (5)
tonyfast/nsf-goali
Aug 2014 - Jan 2015
Contributions:189 commits, 55 pushes in 5 months
npaulson/pduq
Jun 2019 - Sep 2019
Python package for uncertainty quantification in CALPHAD
Contributions:34 commits, 24 PRs, 29 pushes in 2 months
pythonuncertainty-quantificationcalphaduncertaintypython-package
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