I am a PhD student advised by Prof. Bill Dally at Stanford University. Before coming to Stanford, I received my bachelor degree from the Department of Electronic Enginnering, Tsinghua University.
I am interested in efficient deep learning algorithms for video data. Previously I have also worked on neural network compression, including pruning and quantization methods.
Huizi Mao, Taeyoung Kong, William J Dally. CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video. SysML 2019. pdf
Huizi Mao, Song Han, Jeff Pool, Wenshuo Li, Xingyu Liu, Yu Wang, William J Dally. Exploring the Regularity of Sparse Structure in Convolutional Neural Networks. CVPR workshop 2017. pdf
Song Han, Xingyu Liu, Huizi Mao, Jing Pu, Ardavan Pedram, Mark Horowitz, William J. Dally. “EIE: Efficient Inference Engine on Compressed Deep Neural Network”. ISCA 2016.
Huizi Mao, Song Yao, Tianqi Tang, Boxun Li, Jun Yao, Yu Wang. Towards Real-Time Object Detection on Embedded Systems. IEEE Transactions on Emerging Topics in Computing, vol.PP, no.99, pp.1-1.
Song Han, Huizi Mao, William J. Dally. Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding. ICLR 2016 (Best Paper Award).
CS230, Course Assistant, Fall 2019
CS228, Course Assistant, Winter 2020