Profile

Xin Yu is a Ph.D. candidate in Population, Health, and Place (PHP) program at the Spatial Science Institute (SSI), University of Southern California (USC). She received her bachelor’s degree in Spatial Informatics at Wuhan University, China, and M.S in Spatial Data Science at USC.

Throughout her Ph.D. studies, Xin’s research mainly focused on environmental epidemiology, with an emphasis on the susceptibility of air pollution-associated autism risk in early childhood. She is interested using various statistical and causal inference models (Cox regression models, G-computation causal inference, multilevel regression, etc.) to examine the interaction between air pollution and other environmental factors, such as neighborhood social context, maternal immune activation during pregnancy, in relation to child neurodevelopment.

Xin is passionate about utilizing statistical and data science methodologies to address real-world health challenges related to the total environment people are interacting with. Her fervor lies in using her expertise to bridge gaps in healthcare disparities and improve the well-being of underserved communities.

Education

M.S., Spatial Data Science, University of Southern California
Bachelor of Engineering, Spatial informatics & Digitalized Technology, Wuhan University, China

Selected peer-reviewed articles

 Yu, X., Rahman, M. M., Carter, S. A., Lin, J. C., Chow, T., … & Hackman A. Daniel (2023). Neighborhood Disadvantage and Risk for Autism Spectrum Disorder in a Population with Health Insurance. JAMA Psychiatry. (Under review)

Yu, X., Rahman, M. M., Carter, S. A., Lin, J. C., Zhuang, Z., Chow, T., … & Xiang, A. H. (2023). Prenatal Air Pollution, Maternal Immune Activation, and Autism Spectrum Disorder. Environment International, 108148.

Yu, X., Rahman, M. M., Wang, Z., Carter, S. A., Schwartz, J., Chen, Z., … & McConnell, R. (2022). Evidence of susceptibility to autism risks associated with early life ambient air pollution: A systematic review. Environmental Research, 208, 112590.

Modad, B. A. A., Yu, X., Song, H. J., Chiang, Y. Y., & Molisch, A. F. (2022, December). Cell-by-Cell Line-of-Sight Probability Models Based on Real-World Base Station Deployment. In GLOBECOM 2022-2022 IEEE Global Communications Conference (pp. 4782-4787). IEEE.