Data Analytics & AI
Data analytics and artificial intelligence programs and research at U of T Engineering is reshaping processes to improve lives and generate value for people around the world.
We lead a national network of researchers from academia and industry that are designing computer chips that are optimized for artificial intelligence.
- Artificial Intelligence
- Augmented Reality
- Autonomous Vehicles
- Bioinformatics
- Communications
- Computing Systems (from Internet of Things to hardware and software)
- Computer Architecture
- Computational Medicine
- Cybersecurity
- Data Mining
- Fintech
- Intelligent Robotic Systems
- Intelligent Transportation
- Machine Learning
- Neural Networks
- Smart City Platforms
The Vector Institute strives to attract the best global talent focused on research excellence in deep learning and machine learning. Its researchers and academic partners are part of a vibrant community of innovative problem-solvers, working across disciplines on both curiosity-driven and applied research.
Centre for Management of Technology and Entrepreneurship
CMTE is a research leader in communications technology for the Canadian financial services industry. Researchers collaborate with national financial institutions to conduct research into next-generation financial technology.
Computer Hardware for Emerging Sensory Applications
COHESA is a strategic partnership between 19 leading research groups across Canada and technology companies with a long-term interest in machine learning.
Centre for Analytics and Artificial Intelligence Engineering
CARTE is the hub for collaborations and partnerships in analytics and AI at the Faculty of Applied Science and Engineering. We partner with industry and government to drive collaborative research and provide support to match funds from government sources. Through these partnerships, we also cultivate new experiential learning opportunities for students.
Southern Computing for Innovation
SOSCIP pairs academic and industry researchers with advanced computing platforms to fuel Canadian innovation within the areas of agile computing, health, water, energy, cities, mining, advanced manufacturing, digital media and cybersecurity.
Smart Applications on Virtual Infrastructure
SAVI advances Canada’s Digital Economy Strategy by strengthening the industrial base in information and communications technology (ICT) through the active participation of its partners.
Study Data Analytics & Artificial Intelligence at U of T Engineering
Our Master of Engineering students can choose from a wide range of technical emphases, including Robotics & Mechatronics and Analytics. Within the Engineering Science program, undergraduates can major in Robotics or Machine Intelligence — the first program of its kind in Canada to specialize in the study, development and application of algorithms that help systems learn from data. Undergraduates in our core engineering disciplines can pursue complementary studies in Robotics & Mechatronics through multidisciplinary minors.
Leading innovation starts here
Connect with our partnerships team to discuss how a partnership with U of T Engineering can benefit your organization.
Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have designed a new chess AI that understands how humans perceive creativity in chess.
This development could lead to chess engines that can find the most creative and clever path to victory in game, rather than just making moves to maximize its win rate. It could also have implications for other creative endeavours that employ AI.
In a recently published study, Professor Michael Guerzhoy (MIE, EngSci) and Kamron Zaidi (EngSci 2T3 + PEY) use techniques such as game trees and deep neural networks to enable chess engines to recognize brilliant moves.
“A chess move can be perceived as brilliant, or creative, when the strategic payoff isn’t clear at first, but in retrospect, the player had to follow a precise path in gaming out all the possibilities to see so far into the future,” says Guerzhoy, who wrote about the research on his Substack.
“We wanted our system to understand human perception of what constitutes brilliance in chess and distinguish that from just winning.”
Most of the current research into chess AI is focused on enabling moves that create a higher chance of winning to maximize the chess engine’s win rate