NSF Funding on Deep Learning in Geosystems

Zhen Liu
Zhen Liu

Zhen (Leo) Liu (CEE) is the principal investigator on a project that has received a $227,367 research and development grand from the National Science Foundation.

Shiyan Hu (ECE/MTTI) is Co-PI on the project “Image-Data-Driven Deep Learning in Geosystems.” This is a two-year project.

By Sponsored Programs.


Breakthroughs in deep learning in 2006 triggered numerous cutting-edge innovations in text processing, speech recognition, driverless cars, disease diagnosis, and so on. This project will utilize the core concepts underlying the recent computer vision innovations to address a rarely-discussed, yet urgent issue in engineering: how to analyze the explosively increasing image data including images and videos, which are difficult to analyze with traditional methods.

The goal of this study is to understand the image-data-driven deep learning in geosystems with an exploratory investigation into the stability analysis of retaining walls. To achieve the goal, the recent breakthroughs in computer vision, which were later used as one of the core techniques in the development of Google’s AlphaGo, will be studied for its capacity in assessing the stability of a typical geosystem, i.e., retaining walls.

Read more at the National Science Foundation.