Two from MIT awarded 2024 Paul and Daisy Soros Fellowships for New Americans
Fellowship funds graduate studies for outstanding immigrants and children of immigrants.
Fellowship funds graduate studies for outstanding immigrants and children of immigrants.
The MIT-led projects will investigate novel high-performance designs, materials, processes, and assessment methods for an environmentally sustainable microchip industry.
Programming course for incarcerated people boosts digital literacy and self-efficacy, highlighting potential for reduced recidivism.
The grants fund studies of clean hydrogen production, fetal health-sensing fabric, basalt architecture, and shark-based ocean monitoring.
MIT researchers find circadian variations in liver function play an important role in how drugs are broken down in the body.
The advance offers a way to characterize a fundamental resource needed for quantum computing.
For the first time, researchers use a combination of MEG and fMRI to map the spatio-temporal human brain dynamics of a visual image being recognized.
Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.
Engelward, Oliver, Rothman, and Vuletić are recognized for their efforts to advance science.
A communication system whose users reveal only a few verified aspects of their identity can empower less confident participants to speak up, researchers report.
A CSAIL study highlights why it is so challenging to program a quantum computer to run a quantum algorithm, and offers a conceptual model for a more user-friendly quantum computer.
An MIT Values event showcased three women's career journeys and how they are paving the way for the next generation.
The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.