Bias and fairness in data-driven decision-making
Uncovering data and algorithmic bias in urban predictive analytics and developing fair and transparent methods for public resource allocation.
Data for climate action
Advancing energy and carbon modeling to enable data-driven climate policy and energy efficiency investment decisions for more sustainable, resilient, and just cities.
Neighborhood dynamics and inequality
Using large-scale mobility and social media data to understand neighborhood change and community connectedness, and to develop privacy-preserving approaches to geolocational analytics.
AI for city management
Building computational methods to support efficient, equitable, and sustainable city operations.