Cristopher Ubal
Hydrogen Researcher at Eindhoven University of Technology
Amsterdam, North Holland, Netherlands
Summary
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Rockstar🎓
Top SchoolCristopher Ubal is a hydrogen researcher and mechanical engineer with four years of experience applying CFD, machine learning and optimization to energy and combustion problems. Currently a PhD candidate at Eindhoven University of Technology, he develops adjoint-design optimization for hydrogen burners using the open-source SU2 suite, contributing back-end C++ work for multicomponent incompressible flow models and creating tutorials and test cases on GitHub. His background spans mechanical, civil and electrical engineering, and he has practical experience deploying ML models for hydrogen flame sensing and data-driven cost estimation in industry. Comfortable teaching complex math and physics topics, he blends rigorous academic research with hands-on software development and a knack for turning experimental data into actionable models.
4 years of coding experience
Bachelor's degree Civil Engineering, Bachelor's degree Civil Engineering at Universidad de ChileMaster's degree Mechanical Engineering Track - Energy Flow and Process Technology, Master's degree Mechanical Engineering Track - Energy Flow and Process Technology at Delft University of TechnologyBachelor's degree Electrical Engineering, Bachelor's degree Electrical Engineering at Universidad Tecnica Federico Santa Maria
Spanish, English
Github Skills (10)
fluid-dynamics10
open-source10
cfengine10
c-language10
cfc10
cprogramming-language10
cfml10
cpp9
c179
python7
Programming languages (5)
Github contributions (5)
su2code/SU2
Mar 2022 - Jan 2023
SU2: An Open-Source Suite for Multiphysics Simulation and Design
Role in this project:
Back-end Developer
Back-end DeveloperContributions:95 reviews, 218 commits, 48 PRs in 10 months
Contributions summary:Cristopher primarily contributed to the back-end development of the SU2 suite, focusing on the incompressible flow solver. Their work involved implementing and refining features related to the fluid mixture model, including composition-dependent density, viscosity, and thermal conductivity. They also worked on adding options for turbulent inlet conditions, thermodynamic pressure, and incorporating the constant Lewis number model.
physicsmultiphysics-simulationpythoncfdsnl-applications
Cristopher-Morales/Master-Thesis---Machine-Learning-scripts
Jul 2022 - Sep 2022
Contributions:27 commits, 27 pushes, 1 branch in 2 months
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