Dina Katabi,the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science, has been named as aGreat Immigrantby the Carnegie Corporation of New York. Katabi, who was born in Syria, is among 38 naturalized citizens from 35 countries of origin who are being celebrated for their contributions to American society.
Over the past year MIT CSAIL has worked with Novartis to test a novel technology for passive, contactless monitoring of physiological signals that may be used to monitor clinical trial patients in their homes.
Robots that have been programmed to see or feel can’t use these signals quite as interchangeably. To better bridge this sensory gap, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a predictive artificial intelligence (AI) that can learn to see by touching, and learn to feel by seeing.
Technology as a vector for positive change | Technology for a better world
CSAIL recently established the TEDxMIT series. The TEDxMIT events will feature talks about important and impactful ideas by members of the broader MIT community.
This event is organized by Daniela Rus and John Werner, in collaboration with a team of undergraduate students led by Stephanie Fu and Rucha Keklar.
We live in a world of wireless signals flowing around us and bouncing off our bodies. MIT researchers are now leveraging those signal reflections to provide scientists and caregivers with valuable insights into people’s behavior and health.
MIT CSAIL unsealed a special time capsule from 1999 after a self-taught programmer Belgium solved a puzzle devised by MIT professor and famed cryptographer Ron Rivest.
A team from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital (MGH) has created a new deep learning model that can predict from a mammogram if a patient is likely to develop breast cancer in the future. They trained their model on mammograms and known outcomes from over 60,000 patients treated at MGH, and their model learned the subtle patterns in breast tissue that are precursors to malignancy.
A new algorithm developed by MIT researchers takes cues from panoramic photography to merge massive, diverse cell datasets into a single source that can be used for medical and biological studies.
A machine-learning model from MIT researchers computationally breaks down how segments of amino acid chains determine a protein’s function, which could help researchers design and test new proteins for drug development or biological research.
