Computing for the health of the planet
The MIT Schwarzman College of Computing welcomes four new faculty members engaged in research and teaching that address climate risks and other environmental issues.
The MIT Schwarzman College of Computing welcomes four new faculty members engaged in research and teaching that address climate risks and other environmental issues.
Undergraduate engineering and computer science programs are No. 1; undergraduate business program is No. 2.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
Lincoln Laboratory Supercomputing Center dataset aims to accelerate AI research into managing and optimizing high-performance computing systems.
Stacy Springs named executive director; Richard Braatz is associate faculty director.
An MIT-developed device with the appearance of a Wi-Fi router uses a neural network to discern the presence and severity of one of the fastest-growing neurological diseases in the world.
Researchers found that an understudied component of computer processors is susceptible to attacks from malicious agents. Then, they developed mitigation mechanisms.
Engineers 3D print materials with networks of sensors directly incorporated.
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.
The faculty members will work together to advance the cross-cutting initiative of the MIT Schwarzman College of Computing.
Inspired by a fiddler crab eye, scientists developed an amphibious artificial vision system with a panoramic visual field.
Algorithms designed to ensure multiple users share a network fairly can’t prevent some users from hogging all the bandwidth.
Researchers use machine learning to automatically solve, explain, and generate university-level math problems at a human level.