U of T ENGINEERING

U of T Engineering News

In March 2026, Sushant Singh (MSE MEng 1T9, MIE PhD 2T6) won the top overall prize at U of T’s Desjardins Startup Prize competition. (photo by Tim Fraser, KITE Studio)

The future of wound healing: Desjardins Prize supports U of T bioprinting startup

Drawing on experience in athletics, marketing, behavioural science and industry, Professor Alex Kaju (ISTEP) brings a practical approach to engineering education. (photo courtesy of Alex Kaju)

‘The goal is to bring the outside world into the classroom’: Meet Professor Alex Kaju

Professor Pakpong Chirarattananon (MIE) draws inspiration from nature to design robots that fly, hop, crawl or seamlessly combine multiple modes of locomotion. (photo courtesy of Pakpong Chirarattananon)

‘Simplicity wins when designing bio-inspired robots’: Meet MIE Professor Pakpong Chirarattananon

Keep up on the latest Engineering News

Subscribe to our Skulematters newsletter on Linkedin

Latest news

Professor Aimy Bazylak is this year’s winner of the McLean Award from the Connaught Fund and the McLean endowment. (Photo: Roberta Baker)

McLean Award recipient Aimy Bazylak is creating new technologies for sustainable energy

August 21, 2020

A steel-tethered airship, known as an aerostat, designed by Solar Ship, Inc. The company is one of several clients whose projects are facilitated by U of T Engineering’s International Virtual Engineering Student Teams (InVEST) initiative. (Photo: Solar Ship, Inc.)

How to work effectively when your team is both global and virtual

August 20, 2020

A precision flight-control test in wind with a hexacopter drone from Professor Steven Waslander‘s (UTIAS) lab. Waslander will use the funding to acquire the latest in motion-capture technology in order to develop next-generation drones. (Photo courtesy of Steven Waslander)

Five U of T Engineering projects receive funding boost for state-of-the-art research tools

August 19, 2020

In this simulation, atoms of five different chemical elements within nanoparticle are represented by different coloured spheres. A computer algorithm developed at U of T Engineering analyzes thousands of possible geometric configurations of these elements in order to predict which ones will have the best performance as industrial catalysts. (Image courtesy Zhuole Lu)

U of T Engineering researchers use machine learning to design smarter industrial catalysts

August 18, 2020

Load more stories