Guodong Zhang (张国栋)

Machine Learning Group
University of Toronto
Vector Institute

Email: gdzhang dot cs at gmail dot com

"Many things are only trivial once you know them." - Herman Chernoff

About Me

I recently joined DeepMind London as a research scientist. I'm also warpping up my PhD thesis at UofT where I was supervised by Roger Grosse.

I work on scalable and multiagent deep learning. I aim to design algorithms and models that train faster, scale better and easier to tune.

Curriculum Vitae

My CV can be downloaded from this link: [CV].

Selected Publications (Google Scholar or Semantic Scholar for Full List)


I am/was a Instructor for
  • CSC 311: Introduction to Machine Learning (2021 Fall)
I am/was a Guest lecturer for
  • CSC 2541: Neural Network Training Dynamics (2021 Winter)
I am/was a TA for
  • CSC 2541: Neural Network Training Dynamics (2021 Winter)
  • CSC 311: Introduction to Machine Learning (2020 Fall)
  • CSC 2515: Machine Learning (2019 Fall)
  • CSC 411: Machine Learning and Data Mining (2018 Fall)
  • CSC 321: Introduction to Neural Networks and Machine Learning (2018 Winter)
  • CSC 384: Introduction to Artificial Intelligence (2017 Fall, 2018 Summer, 2019 Winter)


  • Conference Reviewer: UAI, AISTATS, NeurIPS, ICLR, ICML
  • Journal Reviewer: JMLR

Selected Honors & Awards

Apple PhD Fellowship, 2022.
Borealis AI Fellowship, 2020.
Ontario Graduate Scholarship, University of Toronto, 2020.
CHU Kochen Scholarship, Highest honor for only top 12 student at Zhejiang University, 2016.
Cross-disciplinary Scholars in Science and Technology, UCLA, 2016.
National Scholarship in China, (%1.5), Zhejiang University, 2014, 2015, 2016.
Meritorious Winner, Interdisciplinary Contest in Modeling (ICM), 2016.
1st Prize, (%1.5) China Undergraduate Mathematical Contest in Modeling (CUMCM), 2015.