Scope and Goals: The dynamics of coupled environmental and human systems, and their complexities and connectivity across space and time poses daunting challenges to effective solutions to a variety of mobility and sustainable issues. Data-driven transportation analytics has facilitated the understanding of the dynamics of these systems and their interactions. Analytical advancements have also enabled rigorous analysis of big data available from sensors and citizens to develop effective and timely solutions to challenging urban transportation problems and for policy interventions. This series invites research that sheds light on the opportunities, challenges and solutions of using big mobility data for transportation science and smart cities.
Organization: The Transportation Data Science Seminar Series is sponsored by the Department of Landscape Architecture and Urban Planning, the Texas A&M Transportation Institute and the Texas A&M Institute of Data Science. Please contact Xinyue Ye (LAUP), Michael Martin (TTI), or Xiao Li (TTI) for further information. This series is managed by Texas A&M Urban Data Science Lab.
Zoom Meeting ID: 732 641 0814 Passcode: 575829
Schedule: Seminars will usually take place bi-weekly, with variations to accommodate the academic calendar.