Public Lecture: Overview of Sufficient Dimension Reduction

Thời gian: 14:00 đến 15:00 Ngày 07/10/2025

Địa điểm: Vietnam Institute for Advanced Study in Mathematics (VIASM), 161 Huynh Thuc Khang Street, Hanoi.

Speaker: Linh Nghiem, University of Sydney, Australia

Abstract: Dimension reduction plays an essential role when working with large datasets, especially when the number of variables can be much bigger than the number of observations. In the context of regression, sufficient dimension reduction (SDR) refers to a class of methodologies that both perform dimension reduction on covariates and ensure no information to predict the outcome is lost after the reduction. Combining dimension reduction with the sufficiency principle of statistical inference, SDR has increasingly gained popularity and showed strong performance in large and big datasets. The talk will provide an overview of some popular SDR methods and their recent developments on some complex settings, such as high-dimensional and longitudinal datasets.

About the Speaker: Dr. Linh Nghiem is currently Lecturer (equivalently Assistant Professor) of Statistics at the University of Sydney. As a methodological and applied statistician, Linh is interested in developing novel statistical methodologies for complex settings to address scientific questions using data. His current interests are measurement error models, dimension reduction, and graphical models. His work has been published in the most globally prestigious statistical journals, including Biometrika, Journal of American Statistical Association, Biometrics, and Statistica Sinica.

Language: English
Format: Hybrid

Registration: please click here

Deadline for registration: October 5, 2025

Contact: Ms. Tran My Anh (VIASM) - Email: tmanh@viasm.edu.vn