MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.
Vincent Sitzmann named Junior Bose Award winner
The award is given annually to an outstanding contributor to education from among the faculty members who are being proposed for promotion to associate professor without tenure.
Researchers at MIT, Mass General Brigham, and Harvard Medical School developed a deep-learning model to forecast a patient’s heart failure prognosis up to a year in advance.
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.
Helping scientists run complex data analyses without writing code
Co-founded by an EECS alumnus, Watershed Bio offers researchers who aren’t software engineers a way to run large-scale analyses to accelerate biology.
AI maps how a new antibiotic targets gut bacteria
MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.
New AI system could accelerate clinical research
By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.