Civil and environmental engineering
Civil and environmental engineering

MIT engineers design proteins by their motion, not just their shape

An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.

AI system learns to keep warehouse robot traffic running smoothly

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.

SMART launches new Wearable Imaging for Transforming Elderly Care research group

WITEC is working to develop the first wearable ultrasound imaging system to monitor chronic conditions in real-time, with the goal of enabling earlier detection and timely intervention.

Decoding the Arctic to predict winter weather

With the help of AI, MIT Research Scientist Judah Cohen is reshaping subseasonal forecasting, with the goal of extending the lead time for predicting impactful weather.

Working to eliminate barriers to adopting nuclear energy

Nuclear waste continues to be a bottleneck in the widespread use of nuclear energy, so doctoral student Dauren Sarsenbayev is developing models to address the problem.

New control system teaches soft robots the art of staying safe

MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.

AI and machine learning for engineering design

Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.

Eco-driving measures could significantly reduce vehicle emissions

New research shows automatically controlling vehicle speeds to mitigate traffic at intersections can cut carbon emissions between 11 and 22 percent.

Unpacking the bias of large language models

In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.