Manzhu Yu

Dr. Manzhu Yu received her bachelor's degree in Remote Sensing from Wuhan University in 2012 and doctoral degree in Earth System and Geoinformation Science from George Mason University in 2017. Her dissertation work on "Spatiotemporal Methodologies and Analytics in 4D Extreme Weather Detection - using Dust Storm Events as an Example" confronted the challenges of translating predictions to real-time early warning information and won the Outstanding Ph.D. Award and Best Paper Competition: First Place. She worked as a postdoctoral research fellow at the NSF I/UCRC Spatiotemporal Innovation Center jointly operated at George Mason University, Harvard University, and University of California, Santa Barbara before joining Penn State as an assistant professor of GIScience.

Dr. Yu's research centers on developing spatiotemporal methodologies for the analysis and prediction of extreme weather events, such as wildfires, dust storms, hurricanes, and extreme heat. Specifically, her research seeks to 1) understand the spatiotemporal dynamics of extreme weather events, 2) explore the relationship of these events with other physical and social factors, and 3) integrate heterogeneous data to enhance the predictability, response, and mitigation of extreme weather events.

Within this agenda, her recent work focuses on wildfire, wildfire smoke, and health impacts. Her team has developed deep learning models for wildfire spread and PM2.5 exposure prediction, applied remote sensing to wildfire detection and burn severity mapping, and examined how wildfire smoke affects regional air quality and community health, including its persistent effects on PM2.5 composition across U.S. regions.

Dr. Yu also devotes herself to professional service supporting the communities of GIScience and Geography. She serves on the editorial board of the International Journal of Digital Earth and as Guest Editors for multiple top-tier GIScience journals. She has serves as Penn State's representative to the University Consortium for Geographic Information Science (UCGIS) and served on the program committee for DeepSpatial (ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems) and IEEE Big Data. She was also a member of the organizing committee for the AAG Spatiotemporal Symposium.

Dr. Yu is recruiting graduate students with strong technical backgrounds (remote sensing, spatial data science, atmospheric science, computer science, or a related quantitative field) who are interested in advanced spatial technologies applied to fire science, wildfire smoke transport, and wildfire smoke and health. Please contact her if interested.