MIT CSAIL scientists created an algorithm to solve one of the hardest tasks in computer vision: assigning a label to every pixel in the world, without human supervision.
PhD candidate Jonathan Zong found a lack of systems that earn and maintain public trust in large-scale online research — so he made one himself.
Scientists have created a design and fabrication tool for soft pneumatic actuators for integrated sensing, which can power personalized health care, smart homes, and gaming.
Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.
CSAIL scientists’ novel hardware attack against the Apple M1 chip defeats the last line of security while leaving no trace.
MIT scientists unveil the first open-source simulation engine capable of constructing realistic environments for deployable training and testing of autonomous vehicles.
Researchers created Exo for writing high-performance code on hardware accelerators.
Inspired by a fiddler crab eye, scientists developed an amphibious artificial vision system with a panoramic visual field.
The MIT researcher and former professor discusses how Covid-19 and the influx of virtual technologies created a new medical ecosystem that needs more synchronized oversight.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers created a system that lets robots effectively use grasped tools with the correct amount of force.
A system for monitoring motion and muscle engagement could aid the elderly and athletes during unsupervised physical rehabilitation for injuries or impaired mobility.
Researchers create a method for magnetically programming materials to make cubes that are very picky about what they connect with, enabling more-scalable self-assembly.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
Codon compiles Python code to run more efficiently and effectively while allowing for customization and adaptation to various domains.
Computational tool from MIT CSAIL enables color-changing cellulose-based designs for data visualization, education, fashion, and more.
“DribbleBot” can maneuver a soccer ball on landscapes such as sand, gravel, mud, and snow, using reinforcement learning to adapt to varying ball dynamics.
MIT researchers exhibit a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios.
Codon compiles Python code to run more efficiently and effectively while allowing for customization and adaptation to various domains.
With FabO, PhD student Dishita Turakhia wants to empower students to learn digital fabrication by making video game objects and characters come alive.