Engineers design artificial synapse for “brain-on-a-chip” hardware
Design is major stepping stone toward portable artificial-intelligence devices.
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From undisciplined to interdisciplinary
Math professor Philippe Rigollet, once a “not very disciplined” student, moves between computer science and statistics.
MIT AgeLab's Bryan Reimer wins Autos2050 award
Reimer is recognized for his work in creating a data-driven understanding of how people engage with vehicle automation.
Three EECS professors join leadership team
Saman Amarasinghe and Joel Voldman are named associate department heads; Nancy Lynch is associate department head for strategic directions, a new post.
Citizen scientists discover five tightly packed exoplanets
The planetary system’s dense configuration gives clues to its formation
Startup aims to make vision care more accessible in developing world
Portable device can generate corrective lens prescriptions in areas with no optometry care.
Can computers help us synthesize new materials?
Machine-learning system finds patterns in materials “recipes,” even when training data is lacking.
Inventing the “Google” for predictive analytics
Platform analyzes big data to answer plain-language business queries in minutes instead of months.
Auto-tuning data science: New research streamlines machine learning
A new automated machine-learning system performs as well or better than its human counterparts — and works 100 times faster.
Unlocking marine mysteries with artificial intelligence
Students put their AI software for underwater vehicles to the test on the Charles River.
Calculating the cost of tech-fueled discrimination
Math graduate student’s Data for Black Lives conference provides numbers behind the technologies that enable exclusion.
Try this! Researchers devise better recommendation algorithm
Improved recommendation algorithm should work especially well when ratings data are “sparse.”
Gearing up for the internet of things
Workshop brings together academia and industry to explore how to prepare next-generation wireless for machine-to-machine communication.
MIT brainpower highlighted in Forbes’ 30 Under 30 lists for 2018
Forbes calls this year's 30 Under 30 lists an "encyclopedia of creative disruption."