Exploring the cellular neighborhood
Software allows scientists to model shapeshifting proteins in native cellular environments.
Software allows scientists to model shapeshifting proteins in native cellular environments.
An online model enables users to calculate the least-cost strategy for a specific regional grid under various assumptions; outcomes vary widely from region to region.
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.
An easy-to-use technique could assist everyone from economists to sports analysts.
The team used machine learning to analyze satellite and roadside images of areas where small farms predominate and agricultural data are sparse.
The MIT Orbital Capacity Assessment Tool lets users model the long-term future space environment.
Five multimedia projects communicating climate futures selected for 2023 WORLDING program, online and at MIT.
Placing solutions in the cloud but learning with boots on the ground, GEAR Lab researchers build low-cost, solar-powered irrigation tools to make precision agriculture more accessible.
AI models that prioritize similarity falter when asked to design something completely new.
Lincoln Laboratory is developing a roadmap to streamline system acquisitions and facilitate connectivity across the Southwestern test ranges.
Educators in weeklong MIT workshop mold self-healing metal, bridging materials science and classroom engagement.
A one-week summer program aims to foster a deeper understanding of machine-learning approaches in health among curious young minds.
The challenge involves more than just a blurry JPEG. Fixing motion artifacts in medical imaging requires a more sophisticated approach.
With a new, user-friendly interface, researchers can quickly design many cellular metamaterial structures that have unique mechanical properties.