Zachary Gibbs is a Caltech-trained chemical engineer and data scientist with 12 years of experience applying data-driven modeling, optimization, and automation to oil refining operations at Phillips 66. He builds digital twins, dashboards, and process monitoring systems for units like naphtha reformers and gasoline blending, translating deep process simulation and kinetics expertise into measurable business value. Prior research on thermoelectric materials and hands-on lab work in ALD/MLD give him a rare blend of experimental materials insight and production-scale analytics. An active coder, he contributes to the widely used pymatgen materials library, maintaining and enhancing modules for electronic structure analysis. Based in Bartlesville, OK, he combines domain knowledge across the full data/software stack with practical engineering judgment to drive continuous improvement in refining processes.
12 years of coding experience
9 years of employment as a software developer
California Institute of Technology
BS Chemical Engineering, BS Chemical Engineering at University of Colorado Boulder
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
Role in this project:
Back-end Developer
Contributions:16 commits in 10 months
Contributions summary:Zachary primarily contributed to the `pymatgen` library, focusing on enhancements and maintenance of existing code. The commits indicate changes to the `boltztrap.py` and `structure_analyzer.py` modules, suggesting involvement in materials analysis and electronic structure calculations. They also merged branches and addressed merge conflicts, indicating a role in project integration and code management.
Contributions:8 pushes, 2 branches, 1 comment in 7 years 6 months
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