A data designer driven to collaborate with communities
Associate Professor Catherine D’Ignazio thinks carefully about how we acquire and display data — and why we lack it for many things.
Improving health, one machine learning system at a time
Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.
New AI tool generates realistic satellite images of future flooding
The method could help communities visualize and prepare for approaching storms.
Building an understanding of how drivers interact with emerging vehicle technologies
The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advanced vehicle technology.
A vision for U.S. science success
In a talk at MIT, White House science advisor Arati Prabhakar outlined challenges in medicine, climate, and AI, while expressing resolve to tackle hard problems.
MIT researchers develop an efficient way to train more reliable AI agents
The technique could make AI systems better at complex tasks that involve variability.
Advancing urban tree monitoring with AI-powered digital twins
The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.
A model of virtuosity
Acclaimed keyboardist Jordan Rudess’s collaboration with the MIT Media Lab culminates in live improvisation between an AI “jam_bot” and the artist.
Can robots learn from machine dreams?
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
Four from MIT named 2025 Rhodes Scholars
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
Ensuring a durable transition
Progress on the energy transition depends on collective action benefiting all stakeholders, agreed participants in MITEI’s annual research conference.
Graph-based AI model maps the future of innovation
An AI method developed by Professor Markus Buehler finds hidden links between science and art to suggest novel materials.
3 Questions: Inverting the problem of design
MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.
A causal theory for studying the cause-and-effect relationships of genes
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
A portable light system that can digitize everyday objects
A new design tool uses UV and RGB lights to change the color and textures of everyday objects. The system could enable surfaces to display dynamic patterns, such as health data and fashion designs.