Experiential Learning

MetroBridge

MetroBridge is a university-wide program that empowers students across BU to tackle urban issues, and at the same time, helps city leaders confront key challenges. MetroBridge connects with local governments to understand their priorities, and then collaborates with BU faculty to translate each city’s unique needs into course projects. Students in undergrad and graduate classes engage in city projects as class assignments while working directly with local government leaders during the semester. The goal of MetroBridge is to mutually benefit both the BU community and local governments by expanding access to experiential learning and by providing tailored support to under-resourced cities. Read more about MetroBridge.

BU Hub’s Cross-College Challenge (XCC)

The BU Cross-College Challenge (XCC) is the Hub’s signature project-based course open to juniors and seniors from all 10 undergraduate schools and colleges. A variety of on-campus and community clients (including cities) can present real-world projects, and students work collaboratively on their team project.

BU Spark!

BU Spark! is an initiative to support student driven innovation and entrepreneurship in computer science, computer engineering and related disciplines. BU Spark! aims to help students realize their technical potential by providing access to resources, knowledge, and expert networks to support their innovation journeys. Students participating in BU Spark! have created data science tools for Boston, Chelsea, Everett, Natick, and Revere.

BU URBAN Program

The BU Graduate Program in Urban Biogeoscience and Environmental Health (BU URBAN) is designed to prepare Ph.D. students for careers in academia, government agencies, NGOs, and the private sector. While each career trajectory requires specialized professional skills, this program combines broad training across science, management, policy, communication, and governance.

Urban Data Mechanics

Computer science and computational thinking provide a variety of tools and techniques for facilitating data collection, delivery, processing, and interpretation in application areas like urban informatics and distributed systems (e.g., public infrastructure management, traffic modeling, and smart power grids). In each iteration of a data mechanics course, students apply tools and methods to build libraries, platforms, and applications that work with data sets dealing with aspects of urban environments such as mobility (e.g., walkability), employment, traffic and parking, emissions, energy consumption, public safety, and others. Lists of student projects can be found here.