Linzhu (Lynn) Li

Linzhu (Lynn) Li is a Research Professor in the Civil & Urban Engineering Department at NYU Tandon School of Engineering. Her research focuses on image-based characterization of granular materials, with expertise in 2D/3D optical imaging, Dynamic Image Analysis (DIA), and micro-computed tomography (µCT). She specializes in the accurate characterization of problematic soils such as coastal calcareous sediments and liquefiable sands, with an emphasis on granulometry and particle-scale mechanics. Dr. Li has developed large-scale image datasets and machine-learning frameworks for automatic particle segmentation and classification, and in-situ soil identification. Her work also extends to transparent soil modeling and visualization. She collaborates extensively with Professor Magued Iskander on research related to soil imaging and geotechnical engineering. Their joint work includes a co-authored book Dynamic Image Analysis of Granular Materials published in the Springer Series in Geomechanics and Geoengineering. Dr. Li serves as a Young Editorial Board Member (YEBM) for Geodata & AI (Elsevier) and is a member of the American Society of Civil Engineers (M.ASCE).

Linzhu Li is a Research Assistant Professor at New York University and an Assistant Professor at Bradley University, specializing in geotechnical engineering with a focus on image analysis and machine learning for soil classification. Her research explores the application of dynamic image analysis and deep learning techniques to characterize granular soils, including sand particle morphology, granulometry, and interstitial fluid flow. Li's work emphasizes the use of 2D and 3D imaging technologies to improve the accuracy of soil classification and to understand the effects of mechanical stresses on particle breakage. Her studies also address the visualization of pore fluid flow and the development of automated classification systems for sand types.