Zhengjia Huang is a Staff Machine Learning Engineer with a decade of experience applying deep learning to perception for autonomous systems, currently leading ML efforts at NVIDIA in Sunnyvale. Trained at Carnegie Mellon and ShanghaiTech with research time at MIT, he published audio-visual perception work at ICCV and NeurIPS that recovered object shape and material from sound and built the Sound-20K dataset. At Nuro he delivered a 27x improvement on a core metric, and earlier research internships produced a 25% boost in vehicle lateral prediction and real-time semantic segmentation at 30 FPS. He combines a strong research pedigree with production-grade engineering—designing CNNs for forecasting, sensor fusion, and monocular depth—while favoring creative, end-to-end solutions that move ideas quickly from prototype to deployed systems.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Electronic and Information Engineering, Bachelor's degree, Electronic and Information Engineering at ShanghaiTech University
Special Student Program, Electrical Engineering and Computer Science, Special Student Program, Electrical Engineering and Computer Science at Massachusetts Institute of Technology
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Carnegie Mellon University
Contributions:3 pushes, 1 branch in 2 years 8 months
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Zhengjia Huang - Staff Machine Learning Engineer at NVIDIA