Ziheng Jiang

Ziheng Jiang

Ph.D. Student

University of Washington


Ziheng Jiang is a Ph.D. Student advised by Luis Ceze in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. He also work closely with Tianqi Chen. His current research center around co-designing efficient algorithms and systems for machine learning. He received his Bachelor’s degree from Fudan University, where he was a member of Fudan NLP Lab, working with Xipeng Qiu, and Zheng Zhang.

Besides coding, he also enjoy snowboarding, photography, and badminton:)


  • Machine Learning
  • Large-Scale Computing System


  • PhD in Computer Science, 2018 - Present

    University of Washington

  • BSc in Computer Science, 2013 - 2018

    Fudan University



Research Intern

Google Brain

Jun 2019 – Sep 2019 California

Graduate Research Assistant

University of Washington

Sep 2018 – Present Seattle

Research Intern

Amazon AWS Machine Learning Group

Oct 2017 – Feb 2017 California

Undergraduate Research Assistant

New York University, Shanghai

Apr 2016 – Jan 2017 Shanghai

Undergraduate Research Assistant

Fudan University

Sep 2015 – Jan 2017 Shanghai

Recent Publications

A hardware–software blueprint for flexible deep learning specialization

This article describes the Versatile Tensor Accelerator (VTA), a programmable DL architecture designed to be extensible in the face of …

Relay: A High-Level Compiler for Deep Learning

Frameworks for writing, compiling, and optimizing deep learning (DL) models have recently enabled progress in areas like computer …

TVM: An Automated End-to-End Optimizing Compiler for Deep Learning

There is an increasing need to bring machine learning to a wide diversity of hardware devices. Current frameworks rely on …