Qing Yang

Qing Yang is a software engineer with extensive experience in deep learning and performance optimization for neural networks. From October 2020 to December 2022, Qing worked at NVIDIA as a Deep Learning Library Performance Software Engineer, focusing on designing high-performance CUDA BLAS level-3 kernels and developing a Python-based performance regression library for monitoring CUDA kernel performance. Prior to this, Qing interned at Cadence Design Systems, proposing innovative methods for efficient deep neural networks, and worked as a research assistant at Duke University, contributing to the development of efficient DNN structures and accelerators. Qing is currently employed at Google, specializing in sysinfra performance. Qing holds a PhD in Electrical and Computer Engineering from Duke University and has received advanced degrees in Electrical Engineering from multiple prestigious institutions, including the University of Electronic Science and Technology and Tsinghua University.