Catrina Cuadra

Catrina Cuadra is a data science leader with over a decade of experience tackling complex problems with data-driven solutions. Most recently, she worked for a data science consulting firm managing the data science and analytics team for the Medicare Plan Finder website. Her career bridges the public, private, and academic sectors, where she works to break down silos and foster collaboration. She is passionate about resilient infrastructure and smart city implementation in the face of climate change. Catrina has launched human centric data science programs at Dartmouth College and Darden’s Institute for Business in Society. She holds master’s degrees in anthropology and geomatics from the University of Florida.

Project Description Traditionally reliant on a large team of inspectors and fragmented data, DOT is investing in cutting-edge algorithms to provide more efficient, frequent, and comprehensive insights. This initiative will significantly improve our ability to make informed decisions around mobility and infrastructure by modernizing how we monitor roadway usage and manage physical assets. Planned projects include:

Automated Asset Detection and Inventory: Developing advanced AI models to automatically detect and catalog the agency's physical assets along roadways, such as street lights, signs, and bike racks, using continuously updated point cloud data.
Automated Condition Assessment: Creating machine learning solutions for condition assessment of roadways, curbs, sidewalks, and signs, enhancing our ability to maintain infrastructure proactively.
Automated Volume Estimation: Designing and deploying algorithms to estimate pedestrian, bicycle, and vehicle volumes across NYC’s streets, bike lanes, and sidewalks, utilizing our extensive network of agency camera feeds.