Ricky Tian Qi Chen is a PhD student in the University of Toronto Machine Learning group. His primary research interests are in the areas of representation learning. In particular, he has been developing machine learning models with explainable or interpretable representations, including the use of ordinary differential equations in representing models. He is also broadly interested in questions related to generative modeling, numerical methods for integration, and Bayesian statistics.
Ricky received best paper awards at AABI 2018 and NeurIPS 2018. Previously, he obtained BSc and MSc degrees at the University of British Columbia.