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.

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

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

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

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

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

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

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

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

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 spin-off ModiFace acquired by French cosmetics giant L’Oreal

ModiFace uses augmented reality and artificial intelligence to build advanced facial visualization software

Professor Amy Bilton (MIE), left, and recent graduate Ahmed Mahmoud (MIE MASc 1T6) collaborated on a network of portable, low-cost sensors that can provide real-time data on soil moisture and other quantities important for agriculture. (Photo: Tyler Irving)

Data-driven farming: U of T Engineering spin-off develops low-cost sensors for Nepal

Platform developed by Spero Analytics provides real-time data on soil moisture which can be used to improve agricultural productivity