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 and a Co-PI (2019–2024) 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 focuses on spatiotemporal theories and applications, atmospheric modeling, environmental analytics, big data and cloud computing, and the ability of using the above to solve pressing issues in natural hazards and sustainability. She hopes to continue combat the life and economic costs associated with natural hazards by facilitating more accurate and timely analyses for extreme weather events. She has collaborated actively with researchers in several other disciplines of Geography, Environmental Science, and Computer Science, particularly on the interdisciplinary solutions for natural hazard management and the contributing physical and social factors of these natural hazards.
Dr. Yu also devotes herself to professional services supporting the communities of GIScience and Geography, by serving as the organizing committee for meetings (e.g., AAG Spatiotemporal Symposiums from 2016–2019) and the student board member for the AAG Cyberinfrastructure specialty group. She also commits herself as an active manuscript reviewer for journals such as International Journal of Geographical Information Science, International Journal of Digital Earth, and Computers, Environment, and Urban Systems, among others.
2020-2022, The Arctic in Hot Water: Quantifying Maritime Transport under Declining Sea Ice and Increasing Geopolitical Tension. Penn State Center for Security Research and Education (CSRE), Co-PI
2020-2021, Utilizing geometric deep learning to predict the rapid intensification of tropical cyclones. Penn State Institute for Computational and Data Sciences (ICDS), PI
2020-2021, Integrating Internet of Things (IoT) and satellite observation into localized weather forecast for urban heat island and heatwave. Penn State Institutes of Energy and the Environment (IEE), PI
2019-202, NSF I/UCRC Spatiotemporal Innovation Center, Co-PI, National Science Foundation (NSF)