IDS Interdisciplinary Seminar:
Analyzing time-dependent or sequential data by blending statistical and machine learning techniques
Venue: IDS Seminar Room, P603, Graduate House / Zoom
Mode: Hybrid. Seats for on-site participants are limited. A confirmation email will be sent to participants who have successfully registered.
Abstract
Due to recent developments of information technologies, the data with much bigger sizes and much more complicated forms have been routinely collected from a wide range of scientific fields, and many of them are time-dependent or sequential data. Statistics and machine learning have both developed their own expertise to take care of such type of data: time series analysis and sequential data analysis. These two sub-areas seem to be growing separately, though their targets are more or less the same, and it is of interest to explore the similarity and difference between them. The speaker has conducted researches on time series analysis since 2003 and on sequential data analysis since 2019. He would like to share several pieces of work in these two sub-areas, and some of them are even from the intersection of these two sub-areas.
Speaker
Professor @ Dept of Statistics & Actuarial Science, School of Computing and Data Science, HKU
Professor Guodong Li joined the Department of Statistics & Actuarial Science, The University of Hong Kong, in 2009 as an Assistant Professor, and currently is a Professor. Prior to this, Professor Li had worked at the Division of Mathematical Sciences, Nanyang Technological University, Singapore, as an Assistant Professor since he received his PhD degree in statistics from the University of Hong Kong in 2007. He got his Bachelor and Master degrees in Statistics from Peking University.
His research interests cover the following areas: time series analysis; quantile regression; econometrics; high-dimensional analysis, and machine learning.
For information, please contact:
Email: datascience@hku.hk