Jose Lara
Principal Research Engineer, Model Engineering at National Laboratory of the Rockies
Denver, Colorado, United States
Summary
👤
Senior🎓
Top SchoolJose Lara is a Principal Research Engineer specializing in model engineering for power systems with a decade of experience spanning lab-scale research, industry deployments, and academic instruction. He leads development of the Sienna power simulation platform and has deep technical expertise in microgrid control, energy operations under uncertainty, and optimization-based decision engines. Jose combines hands-on algorithm and solver work—contributing to high-performance Julia packages for power network optimization and DAE solvers—with practical project delivery from hydro rebuilds to EV charging rollouts. He teaches graduate courses on power system analysis and dynamics, bridging research and workforce development. Fluent in English and Spanish (and intermediate Portuguese), he’s comfortable leading multicultural teams under pressure and translating cutting-edge research into deployable grid solutions. An often-overlooked strength is his track record of maintaining and refactoring scientific codebases to improve robustness and long-term compatibility across the energy modeling ecosystem.
10 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Energy and Resources Group - Designated Emphasis in Computational and Data Science and Engineering, Doctor of Philosophy (Ph.D.) Energy and Resources Group - Designated Emphasis in Computational and Data Science and Engineering at University of California, BerkeleyLicentiate degree Electrical and Electronics Engineering, Licentiate degree Electrical and Electronics Engineering at Universidad de Costa Rica UCRMaster of Applied Science (M.Sc.) Electrical and Computer Engineering, Master of Applied Science (M.Sc.) Electrical and Computer Engineering at University of Waterloo
English, Spanish, Portuguese
Github Skills (11)
pow10
differential-equations10
opt10
julia10
optimization10
scientific-machine-learning9
high-performance9
scim9
network8
adaption7
adaptation7
Programming languages (14)
Github contributions (5)
lanl-ansi/PowerModels.jl
Oct 2018 - Oct 2021
A Julia/JuMP Package for Power Network Optimization
Role in this project:
Back-end Developer
Back-end DeveloperContributions:35 commits, 11 PRs, 17 pushes in 3 years
Contributions summary:Jose primarily focused on refactoring and updating the `powermodels.jl` package, a Julia/JuMP package for power network optimization. Their contributions included updating dependencies, removing deprecated solver calls, and fixing deprecations. The commits also involved cleaning up the codebase and removing explicit overloads. This suggests a focus on maintaining and improving the package's compatibility and functionality.
jumppower-networkoptimizationoptimal-power-flowpower
SciML/OrdinaryDiffEq.jl
Mar 2022 - Apr 2022
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 reviews, 18 commits, 2 PRs in 10 days
Contributions summary:Jose primarily worked on initializing and modifying DAE (Differential Algebraic Equation) initialization algorithms within the `ordinarydiffeq.jl` repository. Their contributions involved adapting the code to incorporate and utilize tolerances within the initialization process, and refactoring the code to leverage existing components from the `DiffEqBase` library. The changes focused on the internal workings of the numerical solvers, improving robustness and integration with other parts of the SciML ecosystem. These modifications demonstrate a deep understanding of ODE/DAE solver implementation.
adaptiveodesscientific-machine-learningdifferential-algebraicdifferential
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