Ontario Tech assistant professor Li Yang studies AI tools for cybersecurity in connected systems

Ontario Tech University assistant professor Li Yang is researching how artificial intelligence and machine-learning tools could be used to detect and respond to cyber threats in connected technologies, including smart infrastructure, Internet of Things devices and advanced wireless networks, according to a March 9 university announcement.

The work touches on systems many residents use or rely on daily, from transportation to energy-related technology. As more services depend on interconnected digital networks, security and reliability become more difficult to maintain, the university said.

Yang, who works in Ontario Tech’s Faculty of Business and Information Technology in Oshawa, said interconnected systems “create new opportunities for attackers,” and that it is important to design solutions that “perform reliably in real-world conditions.”

According to the university, Yang’s research explores AI systems designed to identify unusual activity, adapt to changing conditions and support faster responses to potential risks.

The university said his work also includes automated machine-learning methods that allow models to update themselves as networks change, with the goal of detecting new and evolving threats. Another focus is making AI models efficient enough to run continuously on devices with limited computing power.

One area the university highlighted as a near-term application is electric-vehicle charging infrastructure. Ontario Tech said charging networks link drivers, service providers, payment platforms and energy systems, creating multiple points where a system could be compromised.

The university described two broad types of risks for charging networks: threats that emerge through network connections as charging stations communicate with servers that manage sensitive data, and threats that involve physical access to equipment, such as someone inserting a compromised USB device into a charging unit.

The work is supported by the National Cybersecurity Consortium, the university said. Ontario Tech said Yang’s team is developing lightweight AI models, known as “TinyML,” intended to run on small devices such as a Raspberry Pi and monitor charging stations in real time. The university said the next phase involves deploying the models on charging equipment to test how well they detect new or unfamiliar threats as they occur.

Ontario Tech also said Yang supervises more than 10 student researchers working in AI, cybersecurity and responsible computing. In 2025, the IEEE Computer Society named Yang one of Computing’s Top 30 Early Career Professionals, according to the university announcement.