Steve Dai
Research Scientist at NVIDIA
California, United States
Summary
👤
Senior🎓
Top SchoolSteve Dai is a research scientist at NVIDIA with a decade of experience building cross-layer EDA, high-level synthesis, and GPU-accelerated machine learning systems. He combines a PhD from Cornell and an MS from Stanford with hands-on hardware and verification experience from roles at Oracle, Marvell, Lattice, and ViaSat, giving him rare fluency across algorithms, RTL-level design, and performance optimization. At NVIDIA he focuses on efficient deep learning and high-quality HLS, translating research ideas into practical CAD accelerations that run well on modern GPUs. Based in California, he’s equally comfortable publishing research and shipping production-ready tooling, often bridging gaps between software ML stacks and hardware design flows.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Cornell UniversityBachelor of Science - BS, Bachelor of Science - BS at University of California, Los AngelesMaster of Science - MS, Master of Science - MS at Stanford University
chinese (mandarin/cantonese), French, English
Github Skills (20)
dsl10
fpga9
heterogeneous9
python8
rosetta8
vivado8
lattice8
benchmark7
hardware7
synthesis7
infrastructure7
machine-learning7
asic7
compiler6
spectral5
Programming languages (3)
Github contributions (5)
cornell-zhang/rosetta
Apr 2018 - Feb 2019
Rosetta: A Realistic High-level Synthesis Benchmark Suite for Software Programmable FPGAs
Contributions:2 commits, 1 push, 1 comment in 10 months
high-level-synthesisvivadobenchmark-suitefpgashigh-level
cornell-zhang/facedetect-fpga
Dec 2016 - Feb 2017
Contributions:5 commits, 2 pushes in 2 months
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