CS 5834: Fall 2019
Urban Computing


This course introduces various computational approaches for addressing the challenges that arise in urban environments. The course will discuss algorithms for storing, processing and mining data collected from urban settings. The course will consist of a mixture of computational methodologies and urban computing applications. There will be a special focus on topics such as epidemiology, sustainability, transportation, social science, and urban economics. The following topics will be covered: Machine Learning Basics, Network Science, Spatial Modeling, Trajectory Data Mining, Time-Series Analysis, Visual Analytics, Computational Epidemiology, Public Health, Urban Transportation, Environment Monitoring, Computational Sustainability, Crowdfunding.

Course Information

Textbooks and Resources

There is NO required textbook. Various handouts will be provided during the lectures. Recommended reading: See other resources (pointers to datasets, code etc.) here.


Schedule (tentative)

For lecture slides and readings, go here.
  1. Introduction
  2. Machine Learning - Basics
  3. Network Science
  4. Spatial Modeling
  5. Trajectory Data Mining
  6. Time-Series Analysis
  7. Visual Analytics
  8. Computational Epidemiology
  9. Public Health
  10. Urban Transportation
  11. Environment Monitoring
  12. Computational Sustainability
  13. Crowdfunding