Min Kim
Technologist at Sandisk
Irvine, California, United States
Summary
👤
Senior🎓
Top SchoolMin Kim is a Ph.D.-trained technologist with a decade of experience at the intersection of machine learning, digital hardware, and storage systems, currently advancing ML acceleration at Sandisk. He combines RTL-to-physical digital design expertise with software proficiency in C++, SystemC, Python and ML frameworks to deliver FPGA/NPU-accelerated inference and in-storage processing for SSDs. His background includes modeling and statistical error analysis of neural networks, production-focused toolflow experience (Synopsys, Vivado, PrimeTime) and hands-on work with Arm Ethos/U and Corstone IP. Min has driven projects from research prototypes—gem5-based SSD models and MNIST FPGA accelerators—to product planning for computational storage, demonstrating uncommon fluency across simulation, silicon-oriented verification, and ML workload optimization. Based in Irvine, CA, he pairs rigorous academic training with practical delivery and a knack for turning complex device-level constraints into deployable ML acceleration solutions.
10 years of coding experience
6 years of employment as a software developer
Bachelor’s Degree Engineering Science, Bachelor’s Degree Engineering Science at University of TorontoUniversity of California, Irvine
English, KoreanGithub contributions (5)
kmsmoo/Webnovel
Jul 2016 - Aug 2016
Contributions:9 commits, 8 pushes, 1 branch in 27 days
kmsmoo/Distracted_Driver_Detection
Jul 2016 - Jul 2016
Contributions:6 pushes, 1 branch in 3 days
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