Zero-trust architecture may hold the answer to cybersecurity insider threats
MIT Lincoln Laboratory study explores a new approach to securing systems.
MIT Lincoln Laboratory study explores a new approach to securing systems.
Researchers devise an efficient protocol to keep a user’s private information secure when algorithms use it to recommend products, songs, or shows.
Have a question about numerical differential equations? Odds are this CSAIL research affiliate has already addressed it.
Senior Keith Murray combines his interests in neuroscience, computation, and philosophy to better understand human behavior.
Professor Peter Fisher will lead effort to grow and enhance computing infrastructure and services for MIT’s research community.
Researchers create a mathematical framework to evaluate explanations of machine-learning models and quantify how well people understand them.
A machine-learning model can identify the action in a video clip and label it, without the help of humans.
Natural language processing models capture rich knowledge of words’ meanings through statistics.
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.
A new neural network approach captures the characteristics of a physical system’s dynamic motion from video, regardless of rendering configuration or image differences.
Their model’s predictions should help researchers improve ocean climate simulations and hone the design of offshore structures.
Workshop hosted by MIT’s Climate and Sustainability Consortium, MIT-IBM Watson AI Lab, and the MIT Schwarzman College of Computing highlights how new approaches to computing can save energy and help the planet.
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.
MIT researchers can now estimate how much information data are likely to contain, in a more accurate and scalable way than previous methods.
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.