Guodong Zhang (张国栋)

Machine Learning Group
University of Toronto
Vector Institute

Email: gdzhang at cs dot toronto dot edu

About Me

I am now a graduate student in Machine Learning Group at the University of Toronto, advised by Roger Grosse.

My current research interests lie in the intersection of optimization, generalization and uncertainty estimation. In particular, I'm interested in designing second-order optimization algorithms that generalize well and scale well in deep learning. Beyond that, I'm especially interested in developing scalable and flexible uncertainty models so that we can know what we don't know.

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 Prof. Song-Chun Zhu and Ying Nian Wu on energy-based generative models. Besides, I spent half year at Microsoft Research Asia as research intern.


My CV can be found here.

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.
Honorable Winner, Mathematical Contest in Modeling (MCM), 2015.
1st Prize, (%1.5) China Undergraduate Mathematical Contest in Modeling (CUMCM), 2015.
1st Prize, Advanced Math Competition for Undergraduate, 2014.
1st Prize, Physics Competition for Undergraduate, 2014.