Wristband enables wearers to control a robotic hand with their own movements
By moving their hands and fingers, users can direct a robot to play piano or shoot a basketball, or they can manipulate objects in a virtual environment.
New model predicts how mosquitoes will fly
Their flight patterns change in response to different sensory cues, a new study finds. The work could lead to more effective traps and mosquito control strategies.
A better method for planning complex visual tasks
A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.
Improving AI models’ ability to explain their predictions
A new approach could help users know whether to trust a model’s predictions in safety-critical applications like health care and autonomous driving.
Antonio Torralba, three MIT alumni named 2025 ACM fellows
Torralba’s research focuses on computer vision, machine learning, and human visual perception.
A “scientific sandbox” lets researchers explore the evolution of vision systems
The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles.
Deep-learning model predicts how fruit flies form, cell by cell
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
Teaching robots to map large environments
A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.
3 Questions: How AI is helping us monitor and support vulnerable ecosystems
MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.
MIT tool visualizes and edits “physically impossible” objects
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
Robot, know thyself: New vision-based system teaches machines to understand their bodies
Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.
Pedestrians now walk faster and linger less, researchers find
A computer vision study compares changes in pedestrian behavior since 1980, providing information for urban designers about creating public spaces.
A new way to edit or generate images
MIT researchers found that special kinds of neural networks, called encoders or “tokenizers,” can do much more than previously realized.
New tool gives anyone the ability to train a robot
MIT engineers designed a versatile interface that allows users to teach robots new skills in intuitive ways.
Robotic probe quickly measures key properties of new materials
Developed to analyze new semiconductors, the system could streamline the development of more powerful solar panels.