Jinhang Choi is a Senior Deep Learning Software Engineer with a decade of experience specializing in hardware/software co-design for ML acceleration and systematic design automation. He has driven microarchitecture and RTL design for quantization, matrix operations, and DMA engines on FPGAs and spent several years optimizing AI framework performance for large-scale ML accelerators. Currently at NVIDIA after a multi-role tenure at Microsoft, his background spans prototyping NPU designs, BrainWave FPGA offloading, and SDK kernel library design—bridging research-grade microarchitectural insight with production ML software. He holds a Ph.D. from Penn State and has published and engineered data-locality driven CNN acceleration and progressive synthesis techniques for DNN verification. Notably, he pairs deep hardware expertise with practical ML performance tuning, enabling end-to-end acceleration from RTL to framework-level optimizations. Based in Redmond, WA, he brings a rare blend of academic rigor and hands-on systems delivery.
10 years of coding experience
16 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Science and Engineering, Doctor of Philosophy (Ph.D.) Computer Science and Engineering at Penn State University
Master of Engineering (M.Eng.) Computer Science and Engineering, Master of Engineering (M.Eng.) Computer Science and Engineering at Korea University
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Jinhang Choi - Senior Deep Learning Software Engineer at NVIDIA