Zhiling Gu

Zhiling Gu is a Research Fellow at Yale School of Public Health, having earned her Ph.D. in Statistics at Iowa State University. Her work integrates statistical theory with applications in public health and medicine.

Her research spans

• Functional Data Analysis
• Network Analysis
• Spatiotemporal Modeling
• Statistical AI Foundations
• Nonparametric Learning

applied to neuroimaging, electronic health records, and environmental health studies.

Recent publications focus on

• Adaptive spatiotemporal models
• Neuroimaging data processing
• Pandemic forecasting frameworks
• Environmental exposure modeling

with methodological rigor and practical implementation.

Scientific achievements include

• Runner-up in SMI 2023 Student Paper Competition

She has taught

• STAT 305: Engineering Statistics (ISU)
• STAT 226: Business Statistics
• Statistical Computing
• Statistical Learning

and actively engages in academic presentations at conferences like SMI 2024 and CMStatistics 2022.