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Transforming data into knowledge
Creating technology for social change
Looking beyond smart cities
City Science researchers are developing a slew of tangible and digital platforms dedicated to solving spatial design and urban planning c...
Making the invisible visible–inside our bodies, around us, and beyond–for health, work, and connection
Health 0.0
This project is part of a parallel research endeavor with GSK Manufacturing. By simulating how scientists at the Upper Providence site in...
This project is the first of two projects in collaboration with GSK. We are developing a computational simulation that allows a human use...
This is an open source geo spatial exploration tool. Using various public APIs including Open Street Map and the United States Census, we...
We report a novel method that processes biomarker images collected at the point of care and uses machine learning algorithms to provide a...
We built a low-cost and open source 405 nm imaging device to capture red fluorescence signatures associated with the oral biomarker porph...
Two-dimensional radiographs are commonly used for evaluating sub-surface hard structures of teeth, but they have low sensitivity for earl...
Phase 3 clinical trial outcomes used to evaluate new drugs, therapies and vaccines are among the most complex experiments performed in me...
Ira Winder and the Tactile Matrix won the award for best demonstration at the IEEE Future Technologies Conference.
This project focused on pedestrian accessibility in collaboration with Singapore Centre for Liveable Cities. Researchers and planners cam...
A case study implemented by Inioluwa Raji under the guidance of Joy Buolamwini
www.ajlunited.orgAn unseen force is rising—helping to determine who is hired, granted a loan, or even how long someone spends in prison. ...
The Gender Shades project pilots an intersectional approach to inclusive product testing for AI.Algorithmic Bias PersistsGender Shades is...
MIT researchers have developed a system that can produce images of objects shrouded by fog so thick that human vision can’t penetrate it.
Tangible interactive matrix for real-time computation and 3D projection mappingThe Tactile Matrix is a system for an illuminated, machine...
All people are created equal, but in the eyes of the algorithm, not all faces are just yet.A new study from MIT and Microsoft r...
A new review of face recognition software found that, when identifying gender, the software is most accurate for men with light skin...
Examination of facial-analysis software shows error rate of 0.8 percent for light-skinned men, 34.7 percent for dark-skinned women.
New research out of MIT’s Media Lab is underscoring what other experts have reported or at least suspected before: facial recognition tec...
This project depicts the design, deployment and operation of a Tangible Regulation Platform, a physical-technological apparatus made for ...
We recently led a workshop in Saudi Arabia, with staff from the Riyadh Development Authority, to test a new version of our CityScope plat...
Read more about this project hereMIT City Science is working with Hafencity University to develop CityScope for the neighborhood of Rothe...
View the main City Science Andorra project profile.Research in dynamic tools, mix users (citizens, workers) amenities, services, and land...
The Mobility Futures Collaborative in the MIT Department of Urban Studies and Planning (DUSP) and the Changing Places grou...
Developed by Ira Winder with the MIT Centre for Transportation and Logistics, the model seeks to use real population data and create a si...
Facebook volunteers and work-at-home moms might be making city planning decisions, thanks to AI research conducted by MIT scientists. Res...
Using computer vision to examine Google Street View, the researchers analyzed how streets and blocks have changed in five American cities.
Tested with five American cities, Streetchange quantifies the physical improvement or deterioration of neighborhoods.
A recently published paper in the Proceedings of the National Academy of Sciences (PNAS) looks at factors that predict neighborhood change.
Researchers have used machine learning to quantify the physical improvement or deterioration of neighborhoods in five American cities.
Computer vision uncovers predictors of physical urban change
Paiva, Prada, W., (Eds.)., 4738, datePaiva, Prada, W., (Eds.)., 4738, datePaiva, Prada, W., (Eds.)., 4738, date