Data analytics &
artificial intelligence news

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.

Mona Gridseth (left, UTIAS PhD candidate) and Keenan Burnett (EngSci 1T6+PEY, UTIAS MASc candidate) work on Zeus, a self-driving vehicle that recently took the top prize at the first competition of the three-year AutoDrive Challenge™. U of T Engineering’s new Engineering Science major in Machine Intelligence launches this September. It joins an MEng emphasis in Analytics that began January 2018. (Credit: Laura Pedersen)

U of T Engineering launches Canada’s first engineering undergraduate program in Machine Intelligence

July 24, 2018

Students will begin courses in the new major in September 2018

Veneris and team_credit Jessica MacInnis_700

U of T Engineering blockchain project receives funding injection from Connaught Fund

July 20, 2018

Multidisciplinary team unites researchers to apply blockchain technology in fields from law to finance

Professor Moshovos and his team. Front row, left to right: Zissis Poulos, Dylan Malone Stuart, Professor Andreas Moshovos; back row, left to right: Sayeh Sharifymoghaddam, Kevin Siu, Mostafa Mahmoud, Patrick Judd, Alberto Delmas Lascorz, Milos Nikolic. (Credit: Tyler Irving)

Building the computing engines that will power the machine learning revolution

July 19, 2018

New NSERC Strategic Partnership Network focuses on techniques to optimize hardware for artificial intelligence

On the left of each quadrant is a real X-ray image of a patient’s chest and beside it, the syntheisized X-ray formulated by the DCGAN. Under the X-ray images are corresponding heatmaps, which is how the machine learning system sees the images (Image courtesy of: Hojjat Salehinejad/MIMLab).

Training artificial intelligence with artificial X-rays

July 6, 2018

New U of T Engineering research could help AI identify rare conditions in medical images by augmenting existing datasets

Professor Parham Aarabi (ECE) is the CEO and founder of ModiFace, a spin-off company that uses augmented reality (AR) and artificial intelligence (AI) to build advanced facial visualization software for the beauty and medical industries. ModiFace has been acquired by L'Oreal. (Credit: Johnny Guatto)

U of T Engineering AI researchers design ‘privacy filter’ for your photos that disables facial recognition systems

May 31, 2018

New algorithm protects users’ privacy by dynamically disrupting facial recognition tools designed to identify faces in photos

Quantum computing will bring a whole new set of security concerns to the internet — but U of T Engineering advancements in Quantum Key Distribution (QKD) are providing solutions to these emerging challenges. (Creative Commons)

Going the distance with future-proof quantum cryptography

May 22, 2018

Professor Glenn Gulak and team show that error-correction decoding is no longer a computational bottleneck in long-distance Quantum Key Distribution

Zeus, the aUToronto team’s self-driving car, pulls up to the startline at the inaugural competition of the three-year AutoDrive Challenge™ in Yuma, Ariz. (Courtesy: SAE International)

aUToronto team wins first AutoDrive Challenge

May 7, 2018

Three-year international competition challenged eight universities to turn an electric vehicle self-driving by 2020

From left: aUToronto team members Zachary Kroeze (ECE PhD 1T8), Andreas Schimpe, Keenan Burnett (EngSci 1T6+PEY, UTIAS MASc candidate) and Mona Gridseth (UTIAS PhD candidate) in front of their autonomous vehicle, dubbed Zeus . The team is one of eight from universities across North America competing in the international Autodrive Challenge™. (Credit: Laura Pedersen).

aUToronto to compete at international self-driving car competition

April 23, 2018

U of T Engineering student team selected to participate in Autodrive Challenge™ heads to Yuma, Ariz. for first round of three-year competition

Left to right: Sina Bahrami (CivE PhD candidate), Mehdi Nourinejad (CivE PhD 1T7) and Professor Matthew Roorda (CivE) designed an algorithm to optimize the design of parking lots for autonomous vehicles, increasing their capacity by an average of 62 per cent. (Photo: Roberta Baker)

How self-driving cars could shrink parking lots

March 28, 2018

U of T Engineering researchers find that optimizing for autonomous vehicles could increase the capacity of a parking lot by 62 per cent

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Data analytics &artificial intelligence news