Ritchie Zhao

ML Hardware Engineer

Cornell University

Biography

I received my PhD in ECE from Cornell University in May 2020, under Professor Zhiru Zhang. My graduate research is on hardware acceleration for deep neural networks (DNNs), with specific focus on DNN quantization, DNN accelerator design, and high-level synthesis design flows. I am particularly interested in designing DNNs and hardware systems in conjunction for greater synergy.

During my graduate career, I interned at Microsoft Research in Redmond, working with Daniel Lo and Eric Chung on low-precision inference for the Brainwave project. I’m now working full time at Microsoft in the AI and Advanced Architectures team.

My Resume/CV

Interests

Computer Architecture
Digital FPGA Design
High-Level Synthesis
Machine Learning

Education

PhD in Electrical and Computer Engineering

Cornell University
B.S. in Electrical and Computer Engineering, 2014

University of Toronto

Selected Publications

More Publications

Ritchie Zhao, Christopher De Sa, Zhiru Zhang
Overwrite Quantization: Opportunistic Outlier Handling for Neural Network Accelerators, arxiv preprint. October, 2019
Details arXiv
Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting, International Conference on Machine Learning (ICML). June, 2019
Details arXiv PDF Slides Code
Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa, Zhiru Zhang
Building Efficient Deep Neural Networks with Unitary Group Convolutions, Computer Vision and Pattern Recognition (CVPR). June, 2018
Details arXiv PDF
Ritchie Zhao, Weinan Song, Wentao Zhang, Tianwei Xing, Jeng-Hau Lin, Mani Srivastava, Rajesh Gupta, Zhiru Zhang
Accelerating Binarized Convolutional Neural Networks with Software-Programmable FPGAs, Int’l Symp. On Field-Programmable Gate Arrays (FPGA). February, 2017
Details DOI PDF Code

Contact

10333 Main Street Apt 458, Bellevue, WA 98004, USA