Many everyday technologies that help get from place to place and communicate depend on interconnected digital infrastructure. As these networks grow more complex, maintaining security and reliability is becoming increasingly important.

Dr. Li Yang, an Assistant Professor in Ontario Tech University’s Faculty of Business and Information Technology, researches artificial intelligence (AI) and machine learning methods that strengthen cybersecurity across modern digital environments, including smart infrastructure, Internet of Things devices and advanced wireless networks.

“As more technologies that support services such as transportation and energy increasingly rely on interconnected systems, these environments create new opportunities for attackers, and organizations face increasing challenges detecting and responding to cyber threats,” says Dr. Yang. “That makes it important to design solutions that perform reliably in real-world conditions.”

AI approaches for real-world environments

Dr. Yang’s research explores how AI systems can identify unusual activity, adapt to changing conditions and support faster responses to potential risks.

His work includes automated machine-learning approaches that allow models to update themselves and their ability to detect new and evolving cyber threats as networks advance. He also studies methods that make AI models more efficient so they can run continuously on devices with limited computing power.

Protecting emerging infrastructure

One area where this research has immediate application is electric vehicle charging infrastructure. Charging networks connect drivers, service providers, payment platforms and energy systems, creating multiple points where attackers can attempt to compromise a system. Threats can emerge through the network as charging stations communicate with servers that manage sensitive data, and through physical access, such as an attacker inserting a compromised USB device into a charging unit.

Supported by the National Cybersecurity Consortium, Ontario Tech researchers are working to strengthen the cybersecurity of this infrastructure. Dr. Yang’s work plays a key role: his team is developing lightweight AI models (‘TinyML’) that can operate small devices such as Raspberry Pi and monitor charging stations in real time. The next phase of the work will see these models deployed on actual charging equipment to see how well they detect new or unfamiliar threats as they occur.

Training future AI experts

Dr. Yang also supervises more than 10 student researchers who are developing expertise in AI, cybersecurity and responsible computing. Through hands-on research, students gain practical experience designing technologies that prioritize safety, reliability and ethical considerations.

His work has also received international recognition. In 2025, the IEEE Computer Society named Dr. Yang one of Computing’s Top 30 Early Career Professionals.