Samuel Blau is a research scientist and computational chemist with 12 years of experience building automated electronic-structure workflows, graph-based reaction networks, and machine learning models to accelerate energy materials discovery. Trained as a chemical physicist (PhD Harvard), he modeled exciton dynamics in photosynthetic systems and then scaled that expertise to high-throughput molecular simulation and chemically consistent graph architectures for battery interphase prediction. At Berkeley Lab he invents methods that strategically explore electrochemical reaction cascades, combining on-the-fly error correction, QChem integration, and GNNs like BonDNet to push computational design of next-generation storage technologies. Based in Oakland and motivated by climate impact, he is launching a research group that merges theory, software engineering, and automation to translate fundamental photophysics and reaction-network science into practical energy solutions.
11 years of coding experience
15 years of employment as a software developer
Bachelor of Science (BS), Chemistry, Bachelor of Science (BS), Chemistry at Haverford College
Doctor of Philosophy - PhD, Chemical Physics, Doctor of Philosophy - PhD, Chemical Physics at Harvard University
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project.
Contributions:1 review, 6 PRs, 678 pushes in 6 years 1 month
Be a master builder of databases of material properties. Avoid the Kragle.
Contributions:5 PRs, 96 pushes, 19 branches in 4 years 5 months
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