MIT welcomes two from the Heising-Simons Foundation 51 Pegasi b Fellowship for 2022
The fellowship supports research contributing to the field of planetary science and astronomy.
The fellowship supports research contributing to the field of planetary science and astronomy.
Faculty leaders highlight innovations that can close longstanding knowledge gaps and reimagine how the world responds to the climate crisis.
A new technique compares the reasoning of a machine-learning model to that of a human, so the user can see patterns in the model’s behavior.
MIT scientists hope to deploy a fleet of drones to get a better sense of how much carbon the ocean is absorbing, and how much more it can take.
MIT researchers design a robot that has a trick or two up its sleeve.
A new analysis shows how milk-producing cells change over time in nursing mothers.
For individuals who communicate using a single switch, a new interface learns how they make selections, and then self-adjusts accordingly.
Why has it taken the scientific community so long to include sex as a biological variable in research and analysis as a matter of course?
Yogesh Surendranath and his team are bringing powerful techniques of electrochemistry to bear on the problem of designing catalysts for sustainable fuels.
Electric fields may represent information held in working memory, allowing the brain to overcome “representational drift,” or the inconsistent participation of individual neurons.
An efficient machine-learning method uses chemical knowledge to create a learnable grammar with production rules to build synthesizable monomers and polymers.
In his book, “New Industrial Urbanism,” Eran Ben-Joseph looks at the evolving form and function of 21st-century cities.
A new technique could enable a robot to manipulate squishy objects like pizza dough or soft materials like clothing.
Brent Minchew leads two proposals to better understand glacial physics and predict sea-level rise as part of MIT's Climate Grand Challenges competition.
A new technique for removing bias in datasets can enable machine-learning models to make loan approval predictions that are both fair and accurate.