Please use this zoom link for the event.
Please join us for a UW Data Science Seminar event on Thursday, March 3rd from 4:30 to 5:30 p.m. featuring S.M. Labib, Assistant Professor of Data Science & Environmental Health at Utrecht University.
“Applications of spatial and data-driven approaches in urban environmental exposure modeling for public health”
Abstract: Most existing urban environmental health studies measure a limited number of environmental exposures when investigating the associations between health outcomes and built, natural, and transport environments. Additionally, many studies focus exclusively on exposure assessments at the neighborhood scale. Such an approach provides an incomplete understanding of how urban environments influence health and what urban design policies might improve public health. This talk will present multiple case studies illustrating how spatial and data-driven approaches can reduce urban environmental exposure assessment issues. First, I will introduce a novel spatial data-driven modeling technique for mapping multi-exposures of urban greenery and discuss how different exposures to the same environmental feature may indicate varying relations with health outcomes. Second, I will discuss integrating multiple micro-environmental attributes from various sources (e.g., Satellite, OpenStreetMap) into a routable transport network to better model active travel-related behavior (e.g., cycling) and urban exposures at a detailed spatial scale. Third, I will present a process of harmonizing varying urban environmental exposures at a micro-scale to predict observed cycling counts (e.g., extracted from Google Street View images) from multiple global cities using deep and machine learning models. Finally, I will identify critical gaps and possible future directions when using data-driven approaches to investigate the effects of urban environmental exposure on public health
Biography: S.M. Labib is Assistant Professor of Data Science & Environmental Health at Utrecht University and a visiting research associate at the Public Health Modelling Group, in the MRC Epidemiology Unit, University of Cambridge. Labib received his PhD from the University of Manchester (UoM). He was a Postdoctoral Research Associate at the MRC Epidemiology Unit, and he worked as a part-time research assistant for the Horizon 2020 funded RESIN project at UoM. Labib’s primary research focuses on developing novel quantitative spatial analytical approaches associated with geographic information science, spatial data science, and remote sensing for studying urban built-natural environment exposures and transport-related health impact assessments. He utilizes data-driven techniques with big spatial data and high-performance computing to explore the influence of the built environment and active transportation (e.g., cycling) on health outcomes in urban contexts globally. Labib is an active promoter of open science and interdisciplinary research.
The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.
The 2021-2022 seminars will be virtual events, and are free and open to the public.