Random Fields and Spatial Data Analysis

Presenter Information

Hailin Sang, University of Mississippi

Start Date

30-4-2025 11:30 AM

Document Type

Event

Description

Linear random fields are important stochastic models that can help data analysts understand complex systems, quantify risk and uncertainty, and find optimal solutions. The principal investigator (PI) will develop new methods to study long-memory linear random fields. This will be the first research program on random fields and spatial data analysis at the University of Mississippi (UM) and within the state of Mississippi. This fellowship will advance and broaden the scope of the PI's research program beyond UM and the state. The PI will travel with a UM Ph.D. student to Michigan State University (MSU) to work closely with MSU Foundation Professor Yimin Xiao, an expert in stochastic processes and random fields. The PI and Dr. Xiao will organize invited sessions on topics in this field of research at national and international conferences. Dr. Xiao and other experts in this field will visit UM to deliver research talks on the proposed research. Additionally, the PI will develop a graduate course in spatial data analysis at UM. This fellowship will have a lasting impact on the PI's career, strengthen the probability and statistics group at UM, and enhance graduate and undergraduate educatio

Relational Format

report

Recommended Citation

Sang, Hailin, "Random Fields and Spatial Data Analysis" (2025). Showcase of Research and Scholarly Activity. 88.
https://egrove.olemiss.edu/ored_showcase/2025/posters/88