Introducing MIT HEALS, a life sciences initiative to address pressing health challenges
The MIT Health and Life Sciences Collaborative will bring together researchers from across the Institute to deliver health care solutions at scale.
Citation tool offers a new approach to trustworthy AI-generated content
Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.
So you want to build a solar or wind farm? Here’s how to decide where.
MIT engineers show how detailed mapping of weather conditions and energy demand can guide optimization for siting renewable energy installations.
MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16
First organized MIT delegation highlights the Institute's growing commitment to addressing climate change by showcasing research on biodiversity conservation, AI, and the role of local communities.
A new way to create realistic 3D shapes using generative AI
Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.
3 Questions: Community policing in the Global South
International research co-led by Professor Fotini Christia finds an approach lauded in the US works differently in other regions.
Photonic processor could enable ultrafast AI computations with extreme energy efficiency
This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.
The MIT Press releases report on the future of open access publishing and policy
Report aims to “ensure that open science practices are sustainable and that they contribute to the highest quality research.”
Improving health, one machine learning system at a time
Marzyeh Ghassemi works to ensure health-care models are trained to be robust and fair.
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.
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.
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.