Xiaoyan Li

Postdoctoral Researcher

Xiaoyan Li is a computer scientist and mathematical modeller with expertise spanning computer science, data science, and applied mathematics. She holds a Bachelor’s degree in Applied Mathematics, as well as Master’s degrees in Computer Science and Petroleum Engineering. She is currently a Ph.D. candidate in Computer Science at the University of Saskatchewan, scheduled to defend her dissertation in March 2025.

Her research lies at the intersection of machine learning, dynamical system modeling, and applied category theory, with a strong focus on real-world applications. On the application side, her work focuses on developing theory-based machine learning models for public health, enabling policy-making through infectious disease transmission simulations, forecasting, and counterfactual interventions. On the theoretical side, she explores applied category theory for dynamical systems, aiming to design next-generation, modular, and composable modelling frameworks and tools.