Massachusetts Microelectronics Internship Program: a big focus on critical tiny components
EECS Alliance–backed program seeks to get more Massachusetts students into the microelectronics game
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing to move the global conversation about the impact of artificial intelligence from principles to practical…
In-home wireless device tracks disease progression in Parkinson’s patients
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
“Kids are people too!” Throughout his career, Professor Hal Abelson has worked to make information technology more accessible to people of all ages.
Professor Hal Abelson has dedicated his career to making information technology more accessible to all and empowering people — kids, in particular — through computer science. But his…
Collaborative machine learning that preserves privacy
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
AI system makes models like DALL-E 2 more creative
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
MIT named No. 2 university by U.S. News for 2022-23: Undergraduate engineering and computer science programs are No. 1.
MIT has placed second in U.S. News and World Report’s annual rankings of the nation’s best colleges and universities, announced today. As in past years, MIT’s engineering program continues to…
2022 EECS Awards
It’s the summer of 2022, and we want to celebrate the accomplishments and contributions of our incredible EECS community by sharing some of the awards given by the…
New algorithm aces university math course questions
Researchers use machine learning to automatically solve, explain, and generate university-level math problems at a human level.
Using artificial intelligence to control digital manufacturing
Researchers train a machine-learning model to monitor and adjust the 3D printing process to correct errors in real-time.