Guodong Zhang (张国栋)

Machine Learning Group
University of Toronto
Vector Institute

Email: gdzhang at cs dot toronto dot edu

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

Short Bio

I am a second year PhD student in Machine Learning Group at University of Toronto, supervised by Roger Grosse. I also spend 2/3 days a week as a student researcher at Google Brain Toronto this term.

Previously, I received my bachelor degree in Information Engineering from Zhejiang University in 2017. In 2016 summer, I was a visiting student at UCLA, where I worked with Song-Chun Zhu and Ying Nian Wu on energy-based generative models. After my visiting to UCLA, I spent half year interning at Microsoft Research Asia under the supervision of Dr. Jifeng Dai.

I'm currently "full-time" working on Bayesian Deep Learning, and "part-time" interning on Optimization and Generalization of Deep Learning.

Curriculum Vitae

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

Working Paper

Recent Publications (Google Scholar)


I am/was a TA for
  • CSC 411: Machine Learning and Data Mining (2018 Fall)
  • CSC 321: Introduction to Neural Networks and Machine Learning (2017 Winter)
  • CSC 384: Introduction to Artificial Intelligence (2017 Fall, 2018 Summer)


  • Conference Reviewer: UAI 2018, NIPS 2018, ICLR 2019, ICML 2019

Selected Honors & Awards

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.