I am currently an assistant professor at Mila-Quebec AI Institute and HEC Montreal. Prior to that, I was a Postdoc at University of Michigan and Carnegie Mellon University. I also worked at Microsoft Research Asia as an associate researcher between 2014-2016. For more information, please check my CV.

I am looking for very strong students and have multiple positions in my group (including Postdocs, PhDs, MSc, and interns). Students who are interested in working with me please apply through Mila admission or send me an email directly. In particular, I am looking for students with the following background:

  • Graph representation learning, Graph Neural Networks, Knowledge graphs
  • Deep generative models
  • Bioinformatics, medicine

What’s New

  • New!! 3 papers are accepted to NeurIPS’2020!!
  • New!! Received a Tencent AI Lab Rhino-Bird Gift Fund. Thanks Tencent!
  • New!! 4 papers accepted to ICML’20! Congratulations to all my students and collaborators!
  • New!! Received a Amazon Faculty Research Award. Thanks Amazon!
  • New!! Received a Microsoft-Mila collaboration grant on “Towards Combining Statistical Relational Learning and Graph Neural Networks for Reasoning”. Thanks Microsoft!
  • New!! Received a Collaborative Research and Development Grant on “Intelligent Design through Graph Generation with Deep Generative Models and Reinforcement Learning” from National Research Council Canada (NRC). Thanks NRC!
  • New!! I am teaching a new course Deep Learning and Applications this semester!
  • New!! Two papers on graph representation learning for drug discovery are accepted to ICLR’2020!!
  • New!! We released the codes of the pLogicNet model in our NeurIPS’19 paper “Probabilistic Logic Neural Networks for Reasoning”
  • New!! We just released our GraphVite system, which is super effecient and only takes one minute to learn the node embeddings of a graph with one million nodes. It now supports three different tasks including node embeddings, knowledge graph embeddings, and graph&high-dimensional data visualization. For more information, check this link
  • New!! We just released a library of recommender systems with deep neural networks including session-based recommendation, feature-based recommendation, and social recommenddation. For more information, check this link
  • We just released the source codes of our RotatE model. The codes are available at link.
  • I am quite honoured to be named to the first cohort of Canada CIFAR Artificial Intelligence Chairs (CCAI Chair).CIFAR News1 CIFAR News2
  • Tutorial “Graph representation learning” by William L. Hamilton and me has been accepted by AAAI’19. See you at Hawaii!! Slides (Part 0, Part I, Part II, Part III)

Research Interests

  • Deep learning, deep generative models, reinforcement learning
  • Graph representation learning, Graph Neural Networks
  • Natural language understanding and reasoning, Knowledge graphs
  • Drug discovery
  • Recommender systems

Recent Papers

Selected Publications