The Department of Data Science (DS) at City University of Hong Kong (CityUHK) hosted a DS Distinguished Seminar featuring Prof. Jiguo CAO, Canada Research Chair in Data Science and Professor in the Department of Statistics and Actuarial Science at Simon Fraser University, Canada. Prof. Cao delivered a talk on functional nonlinear learning for multivariate functional data.
Prof. Cao's seminar offered a concise overview of recent advances from his research in functional data analysis, focusing on how complex functional objects such as curves and images can be transformed into informative low-dimensional features for downstream statistical learning. He presented three projects covering a progression from supervised functional dimension reduction for censored survival outcomes, with applications to breast cancer risk prediction; to functional nonlinear learning using recurrent neural networks for multivariate curve reconstruction and classification; and to functional autoencoders that simultaneously perform smoothing and nonlinear representation learning for discrete and possibly irregular functional data. Taken together, these works illustrate how classical functional data analysis ideas such as projection, basis representation, and smoothness regularization can be integrated with modern neural-network architectures to improve prediction, classification, denoising, and interpretability in complex biomedical and temporal data applications.
Prof. Cao’s research focuses on functional data analysis and machine learning. In 2021, he received the CRM–SSC Award from the Statistical Society of Canada and the Centre de recherches mathématiques in recognition of his outstanding research contributions.
DS thanks Prof. Cao for his visit and for the engaging interaction with our faculty and students.