The research center, sponsored by the DOE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.
VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
Researchers created polymers that are more resistant to tearing by incorporating stress-responsive molecules identified by a machine-learning model.
This new approach could lead to enhanced AI models for drug and materials discovery.
Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.
ChemXploreML makes advanced chemical predictions easier and faster — without requiring deep programming skills.
Combining powerful imaging, perturbational screening, and machine learning, researchers uncover new human host factors that alter Ebola’s ability to infect.