Canadian AI Industry Track
Canadian AI 2021 invites industry researchers, developers, entrepreneurs and emerging startups to take part in the upcoming Industry Track of the 34th International Conference on Artificial Intelligence in Vancouver, British Columbia.
AI has seen tremendous growth in the past decade driven by the exponential growth of computational power and data. At the same time, AI as a technology has been more accessible than ever with the proliferation of open source libraries, cloud computing, and the tremendous number of online resources for learning. Despite such a fertile environment for AI to flourish, there are still significant challenges of applying AI to solve real-world problems. From data issues to corner cases to algorithmic limitations, shipping industrial AI systems is anything but simple. The aim of the industry track is to connect academic researchers, graduate students, and industry practitioners to better understand the challenges of taking AI from the lab to production.
The theme of this year’s industry track will be AI: From Theory to Practice, focusing on the challenges of applying AI to real-world problems. Industry contributors are invited to submit a proposal for a 20 minute presentation (with an additional 5 minutes of Q&A) on a topic related to using AI to solve a real-world industrial problem. Accepted presenters will also be invited to participate in a moderated panel discussion on the challenges of applying AI in practice.
Note
Due to COVID-19, this track will be offered online.
Program for the Industry Track
Keynote
Pavel Abdur-Rahman
Head of Trusted Data & AI at IBM Canada
"Trusted Data & AI Value Chain Framework"
How are leading enterprises designing Digital Operating Model that promises to create Trust while delivering profitable growth? What are the 5 intelligent workflows, 37 capability models, 7 teams and 18 technology blocks for implementing DataOps and MLOps? Join us to learn the best practices and lessons learned from the production environment battle scars!
Presentations
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Tianle Chen and Kanchana Padmanabhan, Kinaxis Inc
All You Need Is Consistent Promotions
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Spencer Bryson and Jaroslaw Szlichta, Ontario Tech University and IBM Centre for Advanced Studies
Connor Henderson, Ontario Tech University
Parke Godrey, York University and IBM Centre for Advanced Studies
Vincent Corvinelli, Piotr Mierzejewski and Calisto Zuzarte, IBM Ltd.
Database Management Systems Tuning through AI 
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Kuhan Wang, Ali Pesaranghader, Lux Liu and Andrew Brown, Canadian Imperial Bank of Commerce
Applications of Machine Learning at CIBC -
Andre dos Santos and Denilson Barbosa, University of Alberta
Jessie Lamontagne and Paul Edwards, Scotiabank
Synthetic Data Generation of Financial Transactions: a Privacy Driven Roadmap for Unsupervised Learning -
Ivey Chiu, Vincent Zha, Jonah Braverman, Dominic Dupuis and Kuldeep Panjwani, Telus Communications Inc.
Romina Abachi, Amir-Massoud Farahmand and Sedef Akinli Kocak, Vector Institute
An application of Model-Based Reinforcement Learning to reducing energy consumption in TELUS data centres: TELUS/Vector Collaboration on the development of the Energy Optimization System (EOS) -
Farhood Farahnak, Mohammadreza Davari and Leila Kosseim, Concordia University
Elham Mohammadi, Coveo
Transformer Based Text Similarity Engine Optimized for Industrial Use
Schedule - Tuesday May 25th
Note: All times are Eastern Daylight Time (EDT).
3:30 - 3:35 pm: Welcome Address (Brian Keng)
3:35 - 3:55 pm: Keynote
3:55 - 5:05 pm: Industry Presentations (Short Talks - 6 x 10 mins talks (7 mins + 3 mins Q&A))
5:05 - 5:55 pm: Panel/Discussion with Speakers
5:55 - 6:00 pm: Closing Remarks
The full conference program is available here: https://www.caiac.ca/en/conferences/canadianai-2021/program
Each of the speakers will have a long-form video presentation to be posted on the website.
Important Dates
Submission deadline: 26 February, 2021 extended to 8 March 2021
Author notification: 6 April 2021
Conference: 25 May to 28 May 2021
Industry Track: 25 May 2021, 3:30-6:00 pm EST
Proposal
The proposal must include the following:
- Talk title
- Name of the presenter(s), title(s) and company
- Bio of the presenter(s) (max. 100 words per presenter) for the website
- Summary of talk (max. 100 words) for the website
- Detailed description of the talk (max. 500 words) for review
Preference will be given to talks that showcase this year’s theme: AI: From Theory to Practice. Be sure to include details about the industry, problem, and challenges you have faced when deploying AI, in addition to the solutions.
Please submit your proposal for Canadian AI Industry Track using EasyChair: https://easychair.org/conferences/?conf=cai2021
Topics of Interest
The Canadian AI Industry Track welcomes any topic that involves an industrial application of AI. Submissions from a diverse set of industries are highly encouraged (e.g. finance, insurance, supply chain, e-commerce, marketing, manufacturing, energy sector, etc.).
Presentation formats can range from (but are not limited to) algorithmic improvements for industrial applications, interesting applications of AI, case studies describing the practicalities of applying AI, or executive briefings on the state of AI technology in the industry. AI topics may include, but are not limited to:
- Machine Learning (Deep Learning, Statistical Learning etc.)
- Computer Vision
- Data Mining
- Multiagent Systems
- Knowledge Representations and Reasoning
- Human-in-the-loop AI
- Natural Language Processing
- Information Retrieval/Extraction
- Planning and Scheduling
- Reasoning
- Robotics
- Perception
- Multimodal applications
Dates & Venue
Canadian AI 2021: May 25, 2021 to May 28, 2021
The conference will be held in Vancouver, British Columbia and is collocated with the Computer and Robot Vision conference.
Industry Track Chair
Brian Keng, Ph.D.
Chief Data Scientist, Kinaxis Inc.
Adjunct Professor in Data Science, Rotman School of Management, University of Toronto
brian.keng@rotman.utoronto.ca
