The MIT Media Lab, a hallowed digital playground and research center into media technologies, is celebrating its 25th anniversary. We'll ...
"The research is…unique in its approach to enable seeing through dense fog for self-driving cars and augmented driving."
On May 11, 2019 Ramesh Raskar was the doctoral hooding ceremony keynote speaker at UNC Chapel Hill Commencement. He shared the ...
Kumbhathon is a year-round initiative to identify and address the challenges of cities in developing countries. It is not just a hackatho...
MIT Media Lab professor Ramesh Raskar talks about how his high-tech inventions and initiatives can help solve real-world problems.
Technique can capture a scene at multiple depths with one shutter click—no zoom lens needed
MIT Media Lab researchers have created a quick, simple, and inexpensive way to use mobile phones to measure refractive errors of the eye,...
Part of a suite of portable projects for eyecare, CATRA is a new way to detect and quantify cataracts. CATRA is a compact eyepiece attach...
Out of (Line of) Sight, But Not Out of View. The Camera Culture group at the Media Lab has created CORNAR: Looking around Corners with Fe...
eyeMITRA allows anyone to easily and non-invasively explore the back of the eye, opening possibilities for new assessments of eye health ...
Developed by MIT researchers, the technology could be a boon for drivers and driverless cars
MIT researchers have developed a system that can produce images of objects shrouded by fog so thick that human vision can’t penetrate it.
Computational method improves the resolution of time-of-flight depth sensors 1,000-fold.
New 3D camera research from the Media Lab’s Camera Culture group was selected for the Best Papers Special Issue of the ICCV.
View past newsletters to get updates on group research, awards, and initiatives:
Technique could lead to cameras that can handle light of any intensity, audio that doesn’t skip or pop.
Machine learning is helping urbanists confirm–or disprove–long-standing theories about cities.
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.
When a group of forensic dentistry experts set out in 2016 to investigate what may have caused some peculiar holes in a T. rex jaw, they ...
Researchers have used machine learning to quantify the physical improvement or deterioration of neighborhoods in five American cities.
It is not so far-fetched that in the near future, a student will work through a difficult vector calculus problem by using his hands to m...
James Barabas Thesis DefenseHolographic Television: Measuring Visual Performance with Holographic and Other 3D Television TechnologiesWednes