How “information gerrymandering” influences voters
Study analyzes how networks can distort voters’ perceptions and change election results.
Study analyzes how networks can distort voters’ perceptions and change election results.
MIT system “learns” how to optimally allocate workloads across thousands of servers to cut costs, save energy.
“Risk-aware” traffic engineering could help service providers such as Microsoft, Amazon, and Google better utilize network infrastructure.
Along with studying theory, "it's also important to me that the work we are doing will help to solve real-world problems,” says LIDS student Omer Tanovic.
MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.
System better allocates time-sensitive data processing across cores to maintain quick user-response times.
Lincoln Laboratory's lidar data, processed quickly with support from the organization MCNC, helped FEMA assess flooding and damages caused by Hurricane Florence.
“The reason 5G is so different is that what exactly it will look like is still up in the air. Everyone agrees the phrase is a bit of a catch-all.”
Design can “learn” to identify plugged-in appliances, distinguish dangerous electrical spikes from benign ones.
Theoretical study shows how to make wireless localization much more accurate.
New framework guarantees stability of microgrids that supply local power in developing countries.
Using smartphone cameras, system for seeing around corners could help with self-driving cars and search-and-rescue.
Programming language plus simple circuit design could let routers report on their own operation.
CSAIL’s machine-learning system enables smoother streaming that can better adapt to different network conditions.
Given a still image of a dish filled with food, CSAIL team's deep-learning algorithm recommends ingredients and recipes.