Computing science colloquium series at the NRC


The National Research Council of Canada's ( NRC ) Digital Technologies Research Centre hosts a monthly colloquium featuring theoretical and applied topics in computing science, including artificial intelligence, machine learning, deep learning, information theory and technology, data mining and analytics, computational linguistics, computational biology, computer vision, human-computer interaction, cybersecurity, and quantum computing.

Each month, an international or Canadian expert from outside the NRC is invited to give a presentation on a computing science topic to NRC staff. Researchers and post-secondary students in computing science from outside the NRC are also invited to attend. These talks help participants expand their knowledge, inspire discussion and innovation, and encourage potential collaborations with experts from outside the NRC .

To register or for more information:

Contact Yifeng Li by email at Registration is required at least 48 hours in advance of the presentation.

Location of presentations:

Auditorium* of Building M50
1200 Montreal Road
Ottawa, Ontario K1A 0R6

*Visitors must sign in at the front desk, show ID , and will be escorted to and from the auditorium by NRC staff.

Upcoming speakers

Date and time Name Presentation
To be confirmed   To be confirmed

Past speakers

Date and time Name Presentation
April 16, 2019 Alec Jacobson,
Canada Research Chair, Departments of Computer Science and Mathematics,
University of Toronto
Geometry Processing in The Wild
April 12, 2019 Bo Wang,
Vector Institute, Department of Medical Biophysics,
University of Toronto
Integrative Network Analysis for Single-cell RNA -seq and Beyond
March 26, 2019 Guillaume Bourque,
Department of Human Genetics, Genome Quebec Innovation Centre,
McGill University
Scalable Methods for Genomic Analyses and the McGill Initiative in Computational Medicine
January 25, 2019 Yuxi Li,
Attain AI Inc
Deep Reinforcement Learning: Challenges and Opportunities
December 10, 2018 Tamara Broderick,
MIT Computer Science and Artificial Intelligence Laboratory ( CSAIL ), Department of Electrical Engineering and Computer Science, MIT
Automated Scalable Bayesian Inference via Data Summarization
October 19, 2018 Pascal Poupart, David R. Cheriton
School of Computer Science,
University of Waterloo
Probabilistic Generative Deep Learning
October 19, 2018 Stan Matwin,
Institute for Big Data Analytics,
Dalhousie University
AI's Successes and Challenges - a Personal Perspective
August 23, 3018 Alexandre Payeur,
Brain and Mind Research Institute, University of Ottawa
Backpropagating Errors with Burst Coding
June 28, 2018 Peter Wittek,
Vector Institute, Creative Destruction Lab,
University of Toronto
Practical Quantum-Enhanced Machine Learning
May 31, 2018 Mads Karen,
Ottawa Institute of Systems Biology,
University of Ottawa
Intelligent Design: Synthetic Biology and the Evolution of Biotechnology
May 18, 2018 Phil De Luna,
Department of Materials Science and Engineering,
University of Toronto
Accelerated Design of Materials for Artificial Photosynthesis and Solar Fuels