Bennet Meyers is a Senior Researcher at the National Renewable Energy Laboratory and an Adjunct Professor in Electrical Engineering at Stanford, bringing 12 years of experience at the intersection of optimization, signal processing, and photovoltaic systems. He leads DOE-funded projects like PVInsight and REGROW, developing open-source Python tools and advanced computational methods to manage the rapid growth of distributed solar generation. Bennet’s work spans theory to practice—he coauthored a book on signal decomposition with Stephen Boyd and translates cutting-edge mathematics into production-ready code for grid and energy applications. His background combines deep academic training (PhD/MS Stanford, BA Dartmouth) with hands-on PV performance and data-acquisition engineering at SunPower and SLAC. Known for turning large, heterogeneous energy datasets into actionable models, he’s equally comfortable writing scientific software and advising students on practical energy-system courses. A detail that surprises: he pairs rigorous optimization research with practical field-tested expertise in PV test facilities and instrumentation.
12 years of coding experience
17 years of employment as a software developer
BA, cum laude, Physics with Honors and Haseltine Prize, minor in Environmental Sudies, BA, cum laude, Physics with Honors and Haseltine Prize, minor in Environmental Sudies at Dartmouth College
Doctor of Philosophy - PhD, Electrical Engineering, Doctor of Philosophy - PhD, Electrical Engineering at Stanford University
Contributions:34 commits, 16 pushes, 1 branch in 1 year 2 months
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Bennet Meyers - Adjunct Professor at Stanford University