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Jean-Claude Thill
Research Interests
- Sustainable urban development
- Urban transportation
- Social sciences--Network analysis
- Spatial systems
Other Scholars in Department of Geography and Earth Sciences
Jean-Claude Thill is Knight Distinguished Professor of Public Policy. His scholarship touches on various aspects of cities and regions in terms of their socio-economic structures, their housing and employment, as well as transportation infrastructures and mobility behaviors, within the broader theme of sustainability and adaptability in the global context. His research is theoretically informed and empirically grounded. Another dimension of his scholarship fits in geospatial information science, particularly in advancing new methods of spatial analysis, spatial machine learning, social network analysis and complex systems, and big data analytics. His research is global and comparative.
Recent Citations for Jean-Claude Thill
- A mixed-methods analysis of social-ecological feedbacks between urbanization and forest persistence
- Accounting for residential propagule pressure improves prediction of urban plant invasion
- Associations between COVID-19 pandemic, lockdown measures and human mobility : longitudinal evidence from 86 countries
- Boosting computational effectiveness in big spatial flow data analysis with intelligent data reduction
- COVID-19 pandemic severity, lockdown regimes, and people’s mobility : early evidence from 88 countries
- Densification without growth management? Evidence from local land development and housing trends in Charlotte, North Carolina, USA
- Effect of privatization and inland infrastructural development on India's container port selection dynamics
- Exploring feasibility of multivariate deep learning models in predicting COVID-19 epidemic
- Heterogeneous crowd-sourced data analytics
- Machine learning of spatial data
- Machine learning on the COVID-19 pandemic, human mobility and air quality : a review
- Measuring relative opinion from location-based social media : a case study of the 2016 US presidential election
- Non-linear associations between the urban built environment and commuting modal split : a random forest approach and SHAP evaluation
- Predicting the upcoming services of vacant taxis near fixed locations using taxi trajectories
- Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination
- Public perceptions of COVID-19 vaccines : policy implications from us spatiotemporal sentiment analytics
- Spatial analytics based on confidential data for strategic planning in urban health departments
- Spatio-temporal prediction of the COVID-19 pandemic in US counties : modeling with a deep LSTM neural network
- Spatiotemporal evaluation of the built environment's impact on commuting duration
- The role of socioeconomic and climatic factors in the spatio-temporal variation of human rabies in China
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