Kyle Bystrom is a computational scientist and Research Fellow at the Simons Foundation’s Flatiron Institute, bringing a decade of interdisciplinary experience at the intersection of chemistry, materials science, physics, applied math, and computer science with applications in electronics and renewable energy. He holds a PhD in Engineering/Applied Physics from Harvard and has contributed impactful open-source code to flagship projects like PySCF and pymatgen, improving quantum-chemistry performance and materials-analysis interfaces. Kyle’s work combines high-performance backend development, rigorous testing and documentation, and practical tools for DFT and materials modeling—skills honed during roles at Harvard, Berkeley Lab, and UC Berkeley. Based in Cambridge, MA, he pairs deep computational expertise with a habit of shipping reproducible research, and outside the lab he’s a competitive distance runner, a discipline that informs his steady, performance-oriented approach to scientific software.
10 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Chemistry, Bachelor of Science - BS, Chemistry at University of California, Berkeley
Doctor of Philosophy - PhD, Engineering Physics/Applied Physics, Doctor of Philosophy - PhD, Engineering Physics/Applied Physics at Harvard University Graduate School of Arts and Sciences
Contributions:9 reviews, 30 commits, 5 PRs in 1 year 6 months
Contributions summary:Kyle primarily focused on improving the performance and functionality of the PySCF quantum chemistry module. Their contributions include fixing cache allocation and screening issues within the `nr_sgx_direct.c` file. The user also made changes to the `sgx.py` and `sgx_jk.py` files, likely related to implementing or refining the SGX (Stochastic Grid eXchange) method for efficient calculation of the J and K matrices within the Hartree-Fock and DFT calculations. The user's work included refactoring code and adding examples and unit tests.
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:
Backend Developer
Contributions:13 commits, 2 PRs, 2 comments in 16 days
Contributions summary:Kyle primarily focused on developing and modifying core classes and methods within the `pymatgen` library. Their contributions involved creating and refining interface classes, which are likely crucial for materials analysis. Further contributions were focused on documentation and tests, indicating a focus on code clarity and maintainability. Their work aligns with the project's goals of building a robust materials analysis tool.
moleculespythonscienceelectronic-structurepowers
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Kyle Bystrom - Research Fellow at Simons Foundation