Welcome to Canadian AI 2023
The 36th Canadian Conference on Artificial Intelligence (CANAI) took place in-person at McGill University (Montreal, Canada) from June 5 to 9, 2023.
Several awards were given to highly deserving candidates at this conference after careful scrutiny by members of the awards committees. Richard Zemel (Columbia University) received the Lifetime Achievement Award, Xin Wang (University of Calgary) received the Distinguished Service Award, Sriram Ganapathi Subramanian (University of Waterloo) received the Ph.D. Dissertation Award and Puyuan Liu (University of Alberta) received the MSc Thesis Award. Based on the reviewers’ comments and careful consideration of the paper's quality and contributions, the Best Student Paper Award was given to David Beauchemin and Richard Khoury for their paper titled RISC: Generating Realistic Synthetic Bilingual Insurance Contract. The Best Paper Award went to Paritosh Goyal, Chenyang Huang, Amine Trabelsi, and Osmar Zaïane for their paper titled Exploring Preferential Label Smoothing for Neural Network-based Classifiers.
We congratulate all the award winners for their outstanding contributions to AI research and knowledge dissemination.
The full program is available here.
The event is collocated with the Computer and Robot Vision and CSCan conferences. These events (AI·CRV 2023) will bring together hundreds of leaders in research, industry, and government, as well as Canada's most accomplished students. They showcase Canada's ingenuity, innovation and leadership in intelligent systems and advanced information and communications technology. A single registration lets you attend any session in the colocated conferences, which are scheduled in parallel tracks.
The conference proceedings are published on PubPub, an open-source, privacy-respecting, and open access online platform. They are submitted to be indexed and abstracted in leading indexing services such as DBLP, ACM, Google Scholar.
You can consult the proceedings on PubPub's site here: https://caiac.pubpub.org/ai2023.
A Few Pictures of the Event
Dr. Xin Wang, professor at the University of Calgary, received CAIAC’s Distinguished Service Award
The Best Student Paper Award was given to David Beauchemin and Richard Khoury for their paper titled RISC: Generating Realistic Synthetic Bilingual Insurance Contract.
l. to r.: Farhana Zulkernine, David Beauchemin, Richard Khoury
Dr. Richard Zemel, Trianthe Dakolias Professor of Engineering and Applied Science in the Computer Science Department at Columbia University, wins CAIAC Lifetime Achievement Award.
Puyuan Liu, from the University of Alberta, received the Award for best MSc thesis. His work is titled Non-Autoregressive Unsupervised Summarization with Length-Control Algorithms.
l. to r.: Amilcar Soares, Puyuan Liu, Farhana Zulkernine
Osmar Zaïane and his students receive the best paper award at the 2023 Canadian AI conference for their paper Exploring Preferential Label Smoothing for Neural Network-based Classifiers by Paritosh Goyal, Chenyang Huang, Amine Trabelsi and Osmar Zaïane.
l. to r.: Amilcar Soares, Osmar Zaïane, Amine Trabelsi, Farhana Zulkernine
Registration and Venue
Please use the following link to register for Canadian AI 2023. At least one author of a paper to be published in PubPub must register in full (for 3 days). Conference presenters are also encouraged to register for 3 days (the day you are presenting and two other days).
The detailed program of Canadian AI will be posted later.
Please check the detailed program of Canadian AI 2023 regularly for updates.
Presenters are encouraged to use the following templates for their posters and talks to distinguish Canadian AI posters in the multi-conference event. For the talks under the long paper track, you can use your own template if you want to, but for the short paper track, the 5 min talks and the posters should use the given templates.
Social and Networking
We have set up a Slack group which you can join using this link. There is also a LinkedIn Event set up for the event for researchers to connect and build a network.