Intelligent design through graph generation with deep generative models and reinforcement learning project

 

The objective of this research project is to develop general machine learning techniques for graph generation, with the end application of smart design including new material discovery, advanced circuit design, and novel drug invention, amongst many others. Research will focus on deep generative models and reinforcement learning for the generation of graphs with optimized properties. This project is a collaboration with HEC Montreal (HEC) and the NRC. HEC will develop generative frameworks for graph representation based on deep generative models and reinforcement learning. The NRC will provide expertise in machine learning and deep learning.

Project team

Dr. Jian Tang

Dr. Jian Tang is an assistant professor at Mila-Quebec AI Institute and HEC Montreal and is an expert in deep learning, graph representation learning, and graph neural networks with applications in drug discovery, material discovery, and knowledge graph. Dr. Tang is principal investigator on the intelligent design through graph generation with deep generative models and reinforcement learning project.

Find out more about Dr. Tang.

Dr. Harry Guo

Dr. Harry Guo is a research officer at the National Research Council and an adjunct professor in the School of Electrical Engineering and Computer Science at the University of Ottawa. He has extensive expertise in deep generative model and deep reinforcement learning and their applications on data generation.

Find out more about Dr. Guo.