About Me

I am an assistant professor at the Department of Computer Science at the University of Western Ontario. I am also affiliated with the Brain and Mind Institute and the Vector Institute. Before Western, I was a postdoc in the Department of Computer and Information Science at the University of Pennsylvania, with Eric Eaton, and in the Computational Memory Lab, Princeton Neuroscience Institute, Princeton University, with Kenneth Norman. Before that, I spent five wonderful years as a Ph.D student in the Reasoning and Learning Lab, School of Computer Science, McGill University, with Joelle Pineau. Currently, I am primarily working on transfer/multitask/lifelong learning, which is essential for building an intelligent agent in the real world with any amount of versatility. On the application side, I am interested in applying these techniques to brain signal analysis to solve the problems raised in neuroscience, biomedical engineering, neural engineering, healthcare, etc. I am also interested in applying these machine learning techniques to other real-world applications, such as smart grids and financial optimization.


I am always looking for highly motivated, hardworking, and self-driven students to join my research group to conduct research in machine learning.

  • Undergraduate Students: Knowledge of mathematics (e.g., linear algebra, statistics, and calculus) is a must. Knowledge of machine learning (at the level of CS4442) and experience with numerical computing (e.g. Matlab/Python) are also highly desirable. In most cases, I ask for a two-term commitment on a project aimed toward a publication. As my research requires solid mathematical background, I only take 4th-year undergraduate students.
  • Graduate Students: I have multiple PhD positions, starting from Fall 2020. Please apply first to the Department of Computer Science and then write to me. Please make sure you meet the minimum admission requirements. I have a strong preference for the students who have solid background in math and programming (e.g., knowledge of probability and optimization, experience with PyTorch/Tensorflow). In most cases, I will take thesis-based master students only if they 1) come from a top-100 university with a GPA 3.5+/4.0; and/or 2) are willing to continue working towards a PhD with me. A strong publication record in top-tier conferences/journals is a big plus. At Western CS, PhD and thesis-based Master students are fully funded.
  • Exchange Students / Academic Visitors: Unfortunately, I do not currently have the funding to support external exchange students/academic visitors. However, I am happy to hear from prospective students or visitors who would like to work with me to develop a new funding application or who may have access to funds of their own (e.g., CSC scholarships). If our research interests overlap, I am happy to discuss with you the possibility of hosting you at Western.
  • Computational Neuroscience Graduate/Postdocs: Prospective students/postdocs who want to work on computational neuroscience + machine learning may apply for the COMP Postdoctoral and Graduate Fellowship Program, and choose me as a co-advisor.
  • Data Science / Machine Learning Postdocs: Prospective postdocs who want to work on data science + machine learning may apply for the Presidential Data Fellowship.
  • Project Opportunities: If you have a strong machine learning background (i.e., solid knowledge of theoretical machine learning and/or extensive experiences with deep learning) and is looking for a concrete project aiming at publishing papers in top-tier conferences/journals, please send me an email with a detailed CV. I have multiple machine learning projects and we could explore potential collaborations.

Due to the large amount of emails I receive from potential students, I am not able to reply to each individually. I apologize in advance.