Our mission is to change the way urban engineering is done by bridging the gap between Civil Engineering and Computer Science. We focus on developing tools to better understand the urban built environment through pioneering new means to optimize and synthesize multi-modal data collection, storage, and processing. These tools work together to auto-generate high resolution, functional models appropriate for engineering analysis and are aided by datasets of unprecedented density, comprehensiveness, and richness which our group generates.

Our goal is to support both researchers and practitioners working in the urban environment by enabling better research, stronger analyses, and more informed decision-making through data. We aim to provide this support by creating novel methods to leverage the wealth of urban data currently available and technically accessible for collection through a single platform for data storage, management, and querying.

We believe that rich 3D datasets are critical to making cities more livable, safe, and resilient. Such data and the tools to explore them allow engineers to more thoroughly assess risk, planners to envision city scale innovations, and researchers to conduct more spatio-temporally informed investigations.

We approach urban data through the combined lenses of civil engineering and computer science giving us powerful links to real world applications conjoined with a deep understanding of the need for computational robustness and scalability.


What we do

Collect: We collect uniquely optimized, high resolution aerial LiDAR datasets supported by photogrammetry, video, multispectral, and hyperspectral imagery

Build: We build infrastructure to support efficient distributed storage, indexing, querying solutions for conjoining our unique data with data from government agencies, individual researchers, and citizen scientists

Discover: We partner to discover new solutions to urban engineering problems like infrastructure inspection, pedestrian accessibility, wind comfort analysis, building energy management, and city-scale building information modeling.

Share: We share our data, systems, and discoveries through open repositories, collaborations, and our work with students at all levels of the education system.


How we do it

We bring an engineer’s eye for practical solutions to everyday problems.

We believe in the potential of young researchers starting from first research experiences in K-12 programs, we believe that young researchers are the future and take every opportunity to work with them and learn from their fresh perspectives.

We collaborate both deeply and widely over an ever expanding network of collaborators including researchers, government agencies, and companies from fields as diverse as biodiversity, deep learning, material science, and social science.

We always start from the data to develop exclusively data driven techniques which enable our solutions to be applied to urban areas around the world. We avoid a priori assumptions whenever possible starting from the data collection methods and allowing those methods and the data they produce to inform our entire research process.