Ontario Early Researcher Awards support materials for next-generation vehicles and trustworthy applications of machine learning

The metals and manufacturing industries are cornerstones of Canada’s economy, particularly in Southern Ontario. But these days, innovation in industries from automobiles to aerospace is pushing up against the performance limits of conventional metallic alloys, such as steel. Professor Yu Zou (MSE) is helping find a way forward, with support from the Ontario Early Researcher Awards. 

“Metallic components often need to withstand extreme operating conditions, such as high stress and high-temperature environments,” he says. “The demand for new alloys with enhanced mechanical properties has increased. At the same time, many metallic alloys are very expensive and difficult to process into components, leading to considerable materials and energy waste.” 

In response to these challenges, Zou’s Laboratory for Extreme Mechanics and Additive Manufacturing is designing new metallic alloys that have superior mechanical properties surpassing many conventional alloys. The lab produces high-entropy alloy components for aerospace and automotive applications using laser-based additive manufacturing techniques, sometimes also known as metal 3D printing.  

“Additive manufacturing of new metallic materials will allow Ontario manufacturers to use lighter, stronger and high-temperature-stable materials in their products, which will consume less energy and reduce carbon emissions,” he says.  

Zou is one of two U of T Engineering professors to receive an Early Researcher Award (ERA) from the Ontario Ministry of Colleges and Universities in the latest round. The ERA provides five years of critical funding support to early-career scholars as they build their research teams.   

“With this award, I will be able to bring talented students with diverse backgrounds and complementary expertise together to develop next-generation materials and manufacturing processes.” he says. “The program also offers my students the opportunity to work with industry and government partners, preparing them as the next generation of global leaders in this field.” 

Over the years, Zou has built close collaborations with several Ontario manufacturing companies, including Magna International, EXCO Engineering, Integran Technologies, Oetiker Limited, and Mech Solutions. 

“The rapid development of modern industries poses an urgent challenge to speed up the manufacturing parameters for creating new materials and products for demanding applications,” Zou says. 

“This research will provide unique training opportunities for highly qualified personnel and strengthen Ontario’s competitive position in advanced materials and manufacturing.”  

Professor Nicolas Papernot (ECE) is also receiving an ERA for his project, Toward Machine Learning Governance.  

Papernot’s research aims to enable positive applications of machine learning (ML) technology while limiting the risks it creates for society. 

“Society defines what it means for ML technology to be trustworthy, while computer science does so in other ways,” he says. “My research group is attempting to bridge the gap so legislation and regulators can present these technologies in a way that compels the law to adapt, while computer scientists develop the techniques to enforce these new stipulations.”   

One way his research group is doing this is by actively working to understand how ML can bring benefits to patients in the healthcare system while ensuring that the predictions made by ML systems are fair and respectful of the sensitive data they analyze.   

Papernot is also developing mechanisms that enable users to request that their data be removed from an ML system. This interdisciplinary work requires him and his collaborators to understand the societal and technological implications of removing data: how it will affect other users, and how to remove data in a way that doesn’t harm the utility of the system. 

The Early Research Award, along with other funding sources, will give Papernot’s research group additional resources to tackle these ambitious problems.  

“Machine learning can benefit many areas — particularly health care — but only if we deem its results trustworthy,” says Professor Deepa Kundur, Chair of ECE. “This prestigious Early Research Award confirms the value of Papernot’s research to advance ML technology and help situate it within a regulatory framework. Congratulations to Nicolas, as well as Professor Zou.”

“This award is a source of motivation for my students and myself," says Papernot. "It is a recognition of all the contributions my research group has made in the past few years. The external recognition it brings to the choices of research directions we made inspires us to continuing pursuing more high-risk research.”