Steven Mattis

Principal Computational Scientist

Pittsburgh, Pennsylvania, United States
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Summary

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Senior
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Top School
Steven Mattis is a Principal Computational Scientist with 12 years of experience applying mathematical modeling, scientific computing, and machine learning to predict and optimize complex physical systems. Currently leading computational efforts at the Naval Nuclear Laboratory, he has a strong academic foundation with a PhD in Computational and Applied Mathematics from UT Austin and postdoctoral experience in both the US and Germany. Steven specializes in developing new algorithms and turning them into efficient, production-ready implementations alongside multidisciplinary engineering teams. His work emphasizes computational efficiency and statistically grounded predictions, bridging theory and practical engineering constraints in high-stakes environments. Based in Pittsburgh, he brings a rare combination of deep numerical analysis, hands-on software development, and domain knowledge in nuclear-related computational challenges. Colleagues describe him as someone who consistently turns mathematical insight into robust, scalable solutions for real-world problems.
code12 years of coding experience
job15 years of employment as a software developer
bookDoctor of Philosophy - PhD Computational and Applied Mathematics, Doctor of Philosophy - PhD Computational and Applied Mathematics at The University of Texas at Austin
bookBachelor of Science - BS Mathematics, Bachelor of Science - BS Mathematics at University of Notre Dame
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Github Skills (20)

inverse10
gambling10
stochastic10
quantile10
betting10
python9
perl9
proteus9
water8
power-systems8
modeling-tool8
simulation7
complex6
verification6
validation6

Programming languages (3)

C++Jupyter NotebookPython

Github contributions (5)

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smattis/BET-1

Mar 2015 - Aug 2020

Python package for data-consistent stochastic inverse and forward problems.
Contributions:288 pushes, 17 branches in 5 years 6 months
pythonproblemsconsistentbettingstochastic
UT-CHG/BET

Apr 2014 - Aug 2020

Python package for data-consistent stochastic inverse and forward problems.
Contributions:3 releases, 440 commits, 159 PRs in 6 years 5 months
pythonproblemsquantileconsistentbetting
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