Yifan is a PhD candidate at the Institute for Risk Assessment Sciences, Utrecht University, focused on improving fine-scale environmental exposure mapping. She combines street-level imagery with AI-based computer vision to extract human-scale urban environment indicators, supporting more accurate spatial models of exposures such as heat, noise, and greenness. Her background spans GIS, spatial planning and design, and AI-driven urban analytics.
Within Exposome-NL, Yifan contributes to identifying and integrating street-view-derived indicators into current exposure mapping frameworks. This work systematically evaluates their added value as complementary predictors for characterizing the external exposome, with the aim of supporting more accurate and human-centric exposure assessments for public health research and urban planning across the Netherlands.
I hope to make the invisible visible: the everyday environment that people actually experience.
Big Data Computational modelling Geospatial analyses Spatial modelling
The environment we live in has a dominant impact on our health. It explains an estimated seventy percent of the chronic disease burden. Where we live, what we eat, how much we exercise, the air we breathe and whom we associate with; all of these environmental factors play a role. The combination of these factors over the life course is called the exposome. There is general (scientific) consensus that understanding more about the exposome will help explain the current burden of disease and that it provides entry points for prevention and ...
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