Our funding sources are the National Science Foundation (NSF) and the World Bank (WB).

Modeling Urban Poverty and Security in Emerging Regions.
We aim to automatically model poverty and security issues in large cities of developing regions. Our objective is to provide actionable information for policy makers and to have an impact in the cities of the 21st century.

Understanding Behavioral Patterns during Natural Disasters.
We seek to model patterns of displacements and resilience upon natural disasters based on geolocated traces. The aim of this project is to help emergency responders during prevention and response.

Crowdsourced Traffic Information. 
We explore how to extract traffic-related information from social media datasets to inform agencies during snow storms. The purpose of this project is to look for alternative sources of information that can provide insights into human behaviors during mild weather events.

Cycling Safety Maps.
We focus on the automatic computation of cycling safety maps (also known as stress or comfort maps) using various types of open and crowdsourced data. The objective is to provide accurate, city-wide maps that can be used to improve the cycling conditions of cities.