Brandon Bocklund
Staff Scientist at Lawrence Livermore National Laboratory
Livermore, California, United States
Summary
👤
Senior🎓
Top SchoolBrandon Bocklund is a Staff Scientist at Lawrence Livermore National Laboratory with 11 years of experience applying computational materials science to real-world problems. He earned a Ph.D. in Materials Science and Engineering from Penn State (2021) and builds open-source tools—contributing to flagship projects like pycalphad, ESPEI, atomate, and pymatgen—to advance CALPHAD modeling and uncertainty quantification. His work blends high-throughput DFT workflows and thermodynamic modeling (VASP, Thermo-Calc) to accelerate materials design, and he has hands-on experience fixing complex phonon and Debye-model bugs in community codebases. A committed open-science advocate, he frequently publishes code and mentors students through outreach programs, reflecting a rare combination of rigorous research, practical software engineering, and public engagement.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Materials Science and Engineering, Doctor of Philosophy (Ph.D.), Materials Science and Engineering at Penn State UniversityBachelor’s Degree, Materials Science and Engineering, Bachelor’s Degree, Materials Science and Engineering at Michigan State University
Stackoverflow
125reputation
5kreached
1answer
2questions
Github Skills (18)
pytest10
python10
testing10
material-design10
computational-materials-science10
material-components9
material39
json9
materials-informatics9
documentation7
mathematical-optimization6
ipopt6
dask-distributed6
anaconda6
dask6
Programming languages (11)
Github contributions (5)
hackingmaterials/atomate
Nov 2016 - Oct 2017
atomate is a powerful software for computational materials science and contains pre-built workflows.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:39 commits, 16 PRs, 89 comments in 11 months
Contributions summary:Brandon primarily focused on fixing issues related to the Debye model in the GibbsFreeEnergyTask. They addressed problems with force constants, data type conversions for JSON serialization, and incorrect temperature range calculations. The user also resolved a bug in phonon calculation analysis, ensuring that force constants were correctly applied. Additionally, the user contributed to the documentation by adding a Google group link and creating an installation guide.
computational-materials-science
materialsproject/pymatgen
Jun 2017 - Aug 2017
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:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:5 commits, 3 PRs, 10 comments in 2 months
Contributions summary:Brandon primarily contributed to the testing and validation of the `pymatgen` library, specifically focusing on the `PWInput` and `QuasiharmonicDebyeApprox` modules. They fixed existing tests related to `PWInput` and implemented new tests, including those for the anharmonic contribution of Debye temperature calculations. Their contributions involved modifying test files and adjusting testing parameters to account for platform-specific numerical differences.
pymatgenpythonsciencematerials-sciencematerials-informatics
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