MIT community members elected to the National Academy of Engineering for 2026
Seven faculty members, along with 12 additional alumni, are honored for significant contributions to engineering research, practice, and education.
Computer Science and Artificial Intelligence Laboratory (CSAIL)
Helping AI agents search to get the best results out of large language models
EnCompass executes AI agent programs by backtracking and making multiple attempts, finding the best set of outputs generated by an LLM. It could help coders work with AI agents more efficiently.
Antonio Torralba, three MIT alumni named 2025 ACM fellows
Torralba’s research focuses on computer vision, machine learning, and human visual perception.
The philosophical puzzle of rational artificial intelligence
As AI technology advances, a new interdisciplinary course seeks to equip students with foundational critical thinking skills in computing.
Why it’s critical to move beyond overly aggregated machine-learning metrics
New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.
A new way to “paint with light” to create radiant, color-changing items
“MorphoChrome,” developed at MIT, pairs software with a handheld device to make everyday objects iridescent.
Helping companies with physical operations around the world run more intelligently
Founded by two MIT alumni, Samsara’s platform gives companies a central hub to learn from their workers, equipment, and other infrastructure.
Generative AI tool helps 3D print personal items that sustain daily use
“MechStyle” allows users to personalize 3D models, while ensuring they’re physically viable after fabrication, producing unique personal items and assistive technology.
MIT scientists investigate memorization risk in the age of clinical AI
New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.
One pull of a string is all it takes to deploy these complex structures
A new method could enable users to design portable medical devices, like a splint, that can be rapidly converted from flat panels to a 3D object without any tools.
Guided learning lets “untrainable” neural networks realize their potential
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
A new way to increase the capabilities of large language models
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
“Robot, make me a chair”
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
Enabling small language models to solve complex reasoning tasks
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
New method improves the reliability of statistical estimations
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.