Brandon Hong
Data Engineer
Torrance, California, United States
Summary
🤩
Rockstar🎓
Top SchoolBrandon Hong is a data engineer with 11 years of hands-on experience and a UC Berkeley background in Data Science and Statistics, now advancing his skills through an MEng in Applied Data Science at USC Viterbi. He currently builds production data solutions at OPN Healthcare, having progressed from data analyst to data engineer while applying analytics to healthcare workflows. Brandon is an active open-source back-end contributor to prominent materials science projects like pymatgen and atomate, where he developed LAMMPS integration, workflow automation, and custom input generators—work that bridges scientific computing and scalable pipelines. His campus leadership roles (KASA president) and teaching positions (Data 100 intern, Stat 33B reader) demonstrate strong communication and mentorship alongside technical depth. Comfortable translating domain research into production tooling, he brings a rare mix of materials-science code contributions and business-focused analytics experience.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Arts - Data Science and Bachelor of Arts - Statistics, Senior, Bachelor of Arts - Data Science and Bachelor of Arts - Statistics, Senior at University of California, BerkeleyHigh School Diploma, High School Diploma at West High SchoolMaster of Engineering - MEng, Applied Data Science, Master of Engineering - MEng, Applied Data Science at USC Viterbi School of Engineering
Github Skills (11)
lammps10
pymatgen10
workflow-automation10
molecular-dynamics-simulation10
molecular-simulation10
python10
nonlinear-dynamics10
materials-informatics9
computational-materials-science9
science9
fireworks9
Programming languages (4)
Github contributions (5)
materialsproject/pymatgen
Dec 2016 - Jun 2018
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
Back-end DeveloperContributions:30 commits, 5 PRs, 5 comments in 1 year 5 months
Contributions summary:Brandon primarily contributed to the `pymatgen` library, focusing on enhancements to the QChem input/output module and the LAMMPS module. Their work included adding functionality to parse energies from the `gen_scfman` module in QChem 5, adding improper dihedrals to the LAMMPS data parser, and updating the LAMMPS log file parser. They also refactored the `QCInput` class and added corresponding unit tests. These changes indicate a focus on improving the usability and expanding the capabilities of the library.
pymatgenpythonsciencematerials-sciencematerials-informatics
hackingmaterials/atomate
Jun 2017 - Jun 2018
atomate is a powerful software for computational materials science and contains pre-built workflows.
Role in this project:Back-end Developer
Back-end DeveloperContributions:69 commits, 6 PRs, 4 comments in 11 months
Contributions summary:Brandon primarily contributed to the development of the atomate software, a computational materials science tool. Their work involved creating a drone for the LAMMPS molecular dynamics package, which included defining the drone's schema and generating task documents. They also incorporated fireworks for workflow automation and created workflows for running and storing LAMMPS simulations. Furthermore, the user introduced the concept of a custom input file generator.
computational-materials-science
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