Ke Huang is an Associate Professor of Electrical and Computer Engineering at San Diego State University with 11 years of academic and research experience in analog/mixed-signal and RF circuits, machine learning for test optimization, and fault diagnosis. He transitioned from postdoctoral work at UT Dallas—where he developed ML-driven wafer-level spatial correlation models and counterfeit-IC detection methods validated on Texas Instruments probe data—to a faculty role focused on bridging statistical learning and device testing. His work combines rigorous Ph.D.-level microelectronics expertise from Université Grenoble Alpes with practical, industry-relevant solutions that reduce specification testing costs and improve error detection. Based in San Diego, he balances deep technical research with teaching and mentoring, and his eclectic personal interests (from Arch Linux to photography and flight simulation) hint at a pragmatic, hands-on approach to problem solving.
11 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Electrical Engineering, Doctor of Philosophy (Ph.D.), Electrical Engineering at Université Grenoble Alpes
Contributions:86 pushes, 1 issue in 5 years 1 month
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