Urban Science

We integrate data analysis, visualization, sensors, and artificial intelligence into a planning, design, and policy-making context to answer urgent challenges such as the climate crisis, digital citizenship, sustainable urban development, and building a just city.


In the years to come, solutions to the complex global problems, which are increasingly urban, will require an understanding of large amounts of data and a facility with analysis, visualization, sensors, and even the integration of artificial intelligence into planning and policy-making contexts in a democratic and ethical manner. At the same time, the fields of computer science and machine learning can benefit from the urgency and “hands-on” nature of the sorts of challenges presented in policy-making and urban planning contexts and can lead to democratic and ethical innovations of technology. In short: urban planners have excellent problems, and computer scientists have excellent tools.

Areas of Study


The explosion of ubiquitous, inter-connected sensing and computing technologies (epitomized by the smartphone, but more generally represented by the so-called IoT) are rapidly changing the way we understand relevant behaviors in the urban environment, supply conditions, environmental conditions, etc. VR/AR also offer promising, simulation-based data collection techniques. Importantly, these new streams of data pose a wide range of privacy and security concerns, which must be carefully processed by experts and the public at large.

Modeling and Simulation

Broadly understood, computing and computing-enabled capabilities are fundamental to operationalizing mathematical models relevant to understanding relations among built environment-human behavior-outcomes (e.g., health and well-being), environmental systems (e.g., pollution concentrations), economic and financial performance (e.g., investment proforma), etc. Big data and, for example, machine learning techniques offer great promise for enhancing related knowledge creation. At the same time, ever-increasing computing power, epitomized by high performance computing, provides new opportunities for simulating system interactions (e.g., in integrated, high-resolution, agent-based microsimulation tools) to assist in decision-making.


Techniques for visualization in urban planning and design include sketching, drawing, renderings, physical models, maps, videos, etc. Computing is changing the richness, complexity, resolution, and interactivity of visualization and the possibilities for communicating planning concepts. This opens up new opportunities to engage across stakeholder audiences, with new means for instantly and intuitively demonstrating planning impacts and co-creating planning interventions.

Control and Optimization

New and richer sources of real-time data, combined with computing and communication technologies will tighten the urban feedback loop. Scalable, robust, and efficient ways to intervene across the urban landscape can help to better match supply and demand (for mobility, building occupancy, energy networks, etc.), increase safety and security, manage disruptions and emergencies, enhance environmental sustainability, etc. Challenges are multiple, however, and include susceptibility to attack (i.e., cyber-physical security) and the need to balance individual and social objectives. 

Key Themes


Intersection of behavioral science and transportation technology; Urban/transportation microsimulation; Scenario discovery for mobility of the future; Integration of autonomous vehicles and public transit; Future of parking data visualization. 


Democratization of the grid; Data analysis and visualization of environmental hazards and social vulnerability; Behavioral responses to pollution and environmental hazards and associated social costs; Environmental sustainability of urban development and the building sector; Climate data and climate action.

Infrastructure and Information Systems (IIS)

Cybersecurity support for cities; Real estate finance and innovation; Smart sewage systems; Connected infrastructure policy and practice; Place-based infrastructure investment and urban vibrancy dynamics.


Post-disaster housing data analysis; Big data and technology to assess health and happiness outcomes; Integration of urban design and technological measures to increase wellbeing.

Data Action

How do designers and urban planners effectively utilize state-of-the-art computational techniques such as artificial intelligence and machine learning to understand how cities and regions work. How do they incorporate this understanding into their own practice and to implement change in the built environment and communities they work within?