Chen Ying

I am an Assistant Professor, Teaching Stream, in the Department of Electrical and Computer Engineering at the University of Toronto. My work sits at the intersection of software engineering, engineering education, and the changing role of AI in how people learn and work.

I received my B.Eng. in Computer Science and Technology from Wuhan University in 2017 and my Ph.D. in Computer Engineering from the University of Toronto in 2023. After completing my Ph.D., I worked as a researcher in industry before returning to my home department as a faculty member in 2025.

Moving between university and industry changed how I think about engineering education. Academic learning often benefits from carefully scoped problems and structured tasks that make particular concepts and skills easier to develop. Professional engineering introduces additional forms of complexity: working with unfamiliar systems, defining problems that are not fully specified, making trade-offs, and deciding what evidence is needed to trust a solution.

Much of my teaching is shaped by the question of how students can move from learning individual techniques toward developing broader engineering judgment. I am interested in designing courses that provide enough structure for effective learning while also creating meaningful opportunities to work with uncertainty, complexity, trade-offs, and responsibility.

AI adds another dimension to this question. These tools can make sophisticated systems and knowledge more accessible, but they can also make it easier to bypass the reasoning and practice through which understanding develops. Rather than treating AI simply as something to allow or prohibit, I am interested in designing its role in learning: where it can provide useful scaffolding, where students still need meaningful opportunities to practice their own reasoning and technical judgment, and how verification and judgment should change as AI takes on more of the implementation work.

In my teaching, I focus on modern software development, including full-stack web systems, mobile app development, and cloud computing. I approach course design as a form of system design — where lectures, assignments, projects, tools, policies, and student interactions should work together as a coherent whole. I am particularly interested in designing learning experiences that remain meaningful and engaging even at the scale of large graduate courses.

More broadly, I am interested in how engineering education and practice should evolve as the systems we build and the tools we use become increasingly capable. Technologies will continue to change; the more durable challenge is to develop the judgment to decide what to delegate, what to verify, what to understand deeply, and how new capabilities can be used to expand what engineers are able to do.