A technique to improve both fairness and accuracy in artificial intelligence
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.
International award supports early-career scientists and engineers as they pursue interdisciplinary works.
Professor of electrical engineering and computer science will receive additional support to advance his research and career.
Researchers have made strides toward machine-learning models that can help doctors more efficiently find information in a patient’s health record.
A geometric deep-learning model is faster and more accurate than state-of-the-art computational models, reducing the chances and costs of drug trial failures.
Researchers created Exo for writing high-performance code on hardware accelerators.
Researchers develop a comfortable, form-fitting fabric that recognizes its wearer’s activities, like walking, running, and jumping.
Piction Health, founded by Susan Conover SM ’15, uses machine learning to help physicians identify and manage skin disease.
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
An anomaly-detection model developed by SMART utilizes machine learning to quickly detect microbial contamination.
This robotic system uses radio frequency signals, computer vision, and complex reasoning to efficiently find items hidden under a pile.
The second AI Policy Forum Symposium convened global stakeholders across sectors to discuss critical policy questions in artificial intelligence.
Master’s student Chelsi Cocking combines her love for computer science and design in her research and outreach efforts at the Media Lab.
MIT alumni-founded Overjet analyzes and annotates dental X-rays to help dentists offer more comprehensive care.
A new system lets robots manipulate soft, deformable material into various shapes from visual inputs, which could one day enable better home assistants.