KatherineĀ Klise
Principal Member Of The Technical Staff at Sandia National Laboratories
Albuquerque, New Mexico, United States
Summary
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Top SchoolKatherine Klise is a Principal Member of the Technical Staff at Sandia National Laboratories with 12+ years of engineering experience bridging applied mathematics, earth sciences, and software development. She combines an M.S. in Earth and Planetary Sciences and a B.S. in Applied Mathematics to build reliable simulation and modeling tools, contributing backend code and data-science features to prominent open-source projects like Pyomo and the EPA-compatible WNTR water network toolkit. Her work spans parameter estimation, confidence-region methods, and water-distribution simulation documentation and fixes, reflecting both deep technical rigor and clear technical communication. Based in Albuquerque, she pairs domain expertise in geoscience with practical software engineering to deliver auditable, reproducible analysis for critical infrastructure and research applications.
12 years of coding experience
M.S., Earth and Planetary Sciences, M.S., Earth and Planetary Sciences at The University of New MexicoB.S., Applied Mathematics, B.S., Applied Mathematics at Western Washington University
Github Skills (12)
pyomo10
pandas10
parameter-estimation10
python10
documentation10
statistic9
modeling9
data-analysis9
mathematical9
statistics9
scipy8
testing8
Programming languages (3)
Github contributions (5)
USEPA/WNTR
Feb 2014 - Dec 2022
An EPANET compatible python package to simulate and analyze water distribution networks under disaster scenarios.
Role in this project:
Backend Developer & Technical Writer
Backend Developer & Technical WriterContributions:25 releases, 27 reviews, 1378 commits in 8 years 11 months
Contributions summary:Katherine's commits primarily focus on documentation updates and improvements, including documentation updates and fixes for the user manual. They also updated the documentation for features such as water quality simulations and modifications to the network structure, confirming a strong understanding of the project and its functionality. Additionally, the user has been working on bug fixes and corrections related to the underlying code structure and the user interface aspects for features.
simulatepower-systemsmodeling-toolpythonepanet
Pyomo/pyomo
Dec 2018 - Oct 2022
An object-oriented algebraic modeling language in Python for structured optimization problems.
Role in this project:Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:21 reviews, 134 commits, 9 PRs in 3 years 11 months
Contributions summary:Katherine made significant contributions to the Pyomo library, specifically within the context of parameter estimation. The commits involved modifying the `parmest` module to improve functionality, including adding a leave-N-out analysis, and updating plotting functions and test cases. The user's contributions show an understanding of how to implement methods for generating confidence regions and performing likelihood ratio tests in a modeling context, focusing on integrating new features and addressing bugs.
pythonnonlinear-programmingstructuredgurobiproblems
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