Machine learning speeds up vehicle routing
Strategy accelerates the best algorithmic solvers for large sets of cities.
Strategy accelerates the best algorithmic solvers for large sets of cities.
Report led by MIT scientists details a suite of privately-funded missions to hunt for life on Earth's sibling planet.
Chemical engineers created a coating for microbes that could make it easier to deploy the organisms to treat gastrointestinal disease.
The system could help physicians select the least risky treatments in urgent situations, such as treating sepsis.
Study results also show that pancreatic tumor cells can be forced into a more susceptible state by changing their environment.
A new computational simulator can help predict whether changes to materials or design will improve performance in new photovoltaic cells.
Summit features the latest research of women and other underrepresented genders in MIT EECS, along with an opportunity to network, share experiences, and learn.
New technique applied to small computer chips enables efficient vision and detection algorithms without internet connectivity.
New products presented by students at the annual event included a curb-climbing wheelchair attachment and seizure-preventing glasses.
A new “common-sense” approach to computer vision enables artificial intelligence that interprets scenes more accurately than other systems do.
Working directly with oyster farmers, MIT students are developing a robot that can flip heavy, floating bags of oysters, helping the shellfish to grow and stay healthy.
Marcos Berríos ’06, Christina Birch PhD ’15, and Christopher Williams PhD ’12 make up a third of the 2021 NASA astronaut candidate class.
MIT-IBM Watson AI Lab researchers aim to design concrete mixtures that use AI to shrink environmental footprint and cost, while recycling byproducts and increasing performance.
“Evolution Gym” is a large-scale benchmark for co-optimizing the design and control of soft robots that takes inspiration from nature and evolutionary processes.
The new machine-learning system can generate a 3D scene from an image about 15,000 times faster than other methods.