Gavin Weiguang Ding

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Research Team Lead

MASc Engineering Science, Simon Fraser University

I am a Machine Learning Researcher working at Borealis AI at Toronto, ON, Canada. I am interested in a wide range of topics of related to machine learning and artificial intelligence. Currently I spend the majority of my time researching adversarial robustness of deep learning models.

Before joining Borealis AI, I was an Artificial Intelligence Researcher at Kindred AI , where I worked on robotics and machine learning.

I was a research scientist (January 2014 to April 2015) working with Dr. Graham Taylor in School of Engineering, University of Guelph, Canada. There, I worked on deep learning and representation learning.

I got my Master of Applied Science degree from School of Engineering Science at Simon Fraser University (Burnaby, BC, Canada). I worked on medical image analysis with Dr. Mirza Faisal Beg. At SFU, I worked on 2 projects: 1) analysis of spatial-temporal zebrafish heart optical mapping data; 2) automated detection of retinal fluids from OCT images.

I got my Bachelor of Engineering degree from School of Advanced Engineering (academic talent program) at Beihang University (Beijing, China), where I studied Automation, specifically, flight control system.


June 3, 2020

On Minimax Optimality of GANs for Robust Mean Estimation

Twenty Third International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Authors: G. W. Ding , R. Huang , Y. Yu, K. Wu
April 30, 2020

Max-Margin Adversarial Training: Direct Input Space Margin Maximization through Adversarial Training

International Conference on Learning Representations (ICLR), 2020
Authors: G. W. Ding , Y. Sharma, K. Lui , R. Huang
Aug. 10, 2019

On the Effectiveness of Low Frequency Perturbations

International Joint Conference on Artificial Intelligence (IJCAI), 2019
Authors: Y. Sharma, G. W. Ding , M. Brubaker
May 6, 2019

On the Sensitivity of Adversarial Robustness to Input Data Distributions

International Conference on Learning Representations (ICLR), 2019
Authors: G. Weiguang Ding , K. Lui , T. Jin, L. Wang, R. Huang
Dec. 3, 2018

Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds

Neural Information Processing Systems (NeurIPS), 2018
Authors: K. Lui , G. W. Ding , R. Huang , R.J. McCann
April 30, 2018

Improving GAN Training via Binarized Representation Entropy (BRE) Regularization

International Conference on Learning Representations (ICLR), 2018
Authors: Y. Cao , G. W. Ding , K. Lui , R. Huang
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