Lara Ozkan named 2025 Marshall Scholar
The MIT senior will pursue graduate studies in the UK at Cambridge University and Imperial College London.
The MIT senior will pursue graduate studies in the UK at Cambridge University and Imperial College London.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care.
MIT CSAIL director and EECS professor named a co-recipient of the honor for her robotics research, which has expanded our understanding of what a robot can be.
Researchers develop “ContextCite,” an innovative method to track AI’s source attribution and detect potential misinformation.
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.
Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.
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.
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.
Yiming Chen ’24, Wilhem Hector, Anushka Nair, and David Oluigbo will start postgraduate studies at Oxford next fall.
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.
The new Tayebati Postdoctoral Fellowship Program will support leading postdocs to bring cutting-edge AI to bear on research in scientific discovery or music.
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.
“MouthIO” is an in-mouth device that users can digitally design and 3D print with integrated sensors and actuators to capture health data and interact with a computer or phone.