At the invitation of Professor Mou Cuicui and Assistant Professor Peng Xiaoqing from the College of Earth and Environmental Sciences at Lanzhou University, Associate Professor Liu Lin from the Chinese University of Hong Kong will visit our university for academic exchange and deliver a lecture on September 1, 2023. All students and teachers are welcome to attend!

Speaker: Associate Professor Liu Lin, The Chinese University of Hong Kong

Title: Deep Learning for Cryospheric Sciences

Moderator: Professor Mou Cuicui

Time: September 1, 2023 (Friday) at 10:30 AM

Venue: Guanyun Building, Room 1408

Expert Profile:

Liu Lin is an Associate Professor in the Department of Earth and Environmental Science at The Chinese University of Hong Kong. She also serves as the Director of the Graduate Division of Earth and Atmospheric Sciences, a Research Fellow at the Institute of Space and Earth Information Science, and a Research Fellow at the Institute of Energy and Sustainable Development. Her research primarily focuses on applying techniques such as geophysics, geodesy, and deep learning to the study of cryospheric changes. Her research findings have been published in over 50 prestigious international journals, including Nature Climate Change, EPSL, GRL, Remote Sensing of Environment, The Cryosphere, and JGR. She has made significant contributions to advancing the field of geodesy through innovative methods and was awarded the 2021 John Wahr Young Scientist Award by the American Geophysical Union. She is the first young scientist in Hong Kong to receive this prestigious honor. [The John Wahr Young Scientist Award, named after the late internationally renowned geophysicist Professor John Wahr, was first awarded in 2005. It is presented annually to recognize young scholars aged forty or younger who have made significant contributions to the field of geodesy in terms of science, technology, applications, observations, or theory.]

Lecture Profile:

In the era of big data and artificial intelligence, deep learning has emerged as an innovative and important tool in cryosphere remote sensing and modeling and has been applied to nearly all cryospheric components in the Arctic, Antarctica, and high mountain regions. In this talk, I will summarize the exciting and diverse applications of deep learning in cryospheric sciences. Even though most of the published studies in the past five years were demonstrative in nature, these early efforts have successfully proved the effectiveness, robustness, and generalization capability of deep learning in retrieving the patterns of spatial, temporal, and spectral signatures of the cryosphere in remote sensing data, characterizing cryospheric dynamics at local and regional scales, as well as establishing non-linear links between cryospheric processes and various topo-climatic variables.

College of Earth and Environmental Sciences, Lanzhou University

August 30, 2023