Eric Hermes is a Staff Computational Scientist with 12 years of experience applying DFT and microkinetic modeling to heterogeneous catalysis, now building automated, scalable workflows for exascale simulations at Quantum-Si. He holds a Ph.D. in Physical Chemistry from UW–Madison and developed a novel, automated algorithm for locating transition state geometries—implemented in the open-source Sella package—bringing research-grade methods into production-ready Python tooling. His background spans academic research at Sandia National Laboratories and UW–Madison to industry roles where he combines deep theoretical chemistry with software engineering for high-performance computing. Notably, he has contributed to the NWChem project by modernizing its Python interface and socket integrations, demonstrating a rare blend of computational science and practical backend engineering.
12 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Physical Chemistry, Doctor of Philosophy - PhD, Physical Chemistry at University of Wisconsin-Madison
NWChem: Open Source High-Performance Computational Chemistry
Role in this project:
Back-end Developer
Contributions:29 commits, 5 PRs, 9 comments in 1 year 2 months
Contributions summary:Eric contributed to the NWChem repository by implementing and improving the Python interface. Their work included adding Python 2/3 support, performing whitespace cleanup, and making example tests Python 3 compliant. The user also addressed issues related to integer handling, string parsing, and socket communication within the Python bindings. Furthermore, they refactored and enhanced the i-PI socket implementation, demonstrating proficiency in integrating NWChem with external computational tools.
Contributions:10 releases, 265 commits, 17 PRs in 4 years 3 months
minimizationchemistrypythonoptimizationpoint
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