Study of 3.5 million cells from more than 100 human brains finds Alzheimer’s progression — and resilience to disease — depends on preserving epigenomic stability.
Balancing automation and agency, Associate Professor Arvind Satyanarayan develops interactive data visualizations that amplify human creativity and cognition.
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.
New findings could help manufacturers design gels, lotions, or even paving materials that last longer and perform more predictably.
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.
By directly imaging material failure in 3D, this real-time technique could help scientists improve reactor safety and longevity.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
New test could help determine if AI systems that make accurate predictions in one area can understand it well enough to apply that ability to a different area.
The ultrabroadband infrared frequency comb could be used for chemical detection in portable spectrometers or high-resolution remote sensors.
You can adjust the frequency range of this durable, inexpensive antenna by squeezing or stretching its structure.
As large language models increasingly dominate our everyday lives, new systems for checking their reliability are more important than ever.
Training an ever-growing percentage of MIT’s students, the Department of Electrical Engineering and Computer Science relies heavily on dedicated and passionate TAs.