Ian Faust is a Machine Learning Engineer at Intel with 12 years of experience bridging experimental physics and applied ML. He holds a PhD from MIT in Nuclear Engineering and a decade of R&D experience designing, manufacturing and reverse-engineering mechanical and electrical systems alongside production software in Python and C. Ian combines hands-on prototyping—returning a spectrometer to operation and building robust camera and RF diagnostics for fusion experiments—with rigorous statistical ML work (SVM, Bayesian methods, Fisher information, Hessians/Jacobians, bootstrapping) applied to meta-analyses of ~1000 plasma discharges. He previously led big-data analysis at Porsche Engineering and held research roles at Max Planck and MIT. Based in Oberschleißheim, he pairs practical engineering for extreme environments with production ML skills and a dry sense of humor—his GitHub bio: "2020 could be better."
Ishihara Test plates generated using Monte Carlo procedures
Contributions:25 commits, 2 PRs, 19 pushes in 3 years 9 months
monte-carlocarloplatesprocedures
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