Q&A: Phillip Isola on the art and science of generative models
Image-translation pioneer discusses the past, present, and future of generative adversarial networks, or GANs.
Department
Electrical Engineering and Computer Science
Sensor-packed glove learns signatures of the human grasp
Signals help neural network identify objects by touch; system could aid robotics and prosthetics design.
3 Questions: Faculty appointments and the MIT Schwarzman College of Computing
Working group studies options for creating a new set of faculty hires for MIT’s new college.
Developing artificial intelligence tools for all
MIT Quest for Intelligence-sponsored undergraduate research projects demystify AI.
Bringing human-like reasoning to driverless car navigation
Autonomous control system “learns” to use simple maps and image data to navigate new, complex routes.
This robot helps you lift objects — by looking at your biceps
CSAIL system can mirror a user's motions and follow nonverbal commands by monitoring arm muscles.
MIT and U.S. Air Force sign agreement to launch AI Accelerator
New program will focus on rapid deployment of artificial intelligence innovations in operations, disaster response, and medical readiness.
Merging machine learning and the life sciences
Through computing, senior and Marshall Scholar Anna Sappington seeks answers to biological questions.
Twelve MIT students accept 2019 Fulbright Fellowships
Grantees will spend the 2019-2020 academic year pursuing research and teaching opportunities abroad.
3Q: Hal Abelson on empowering kids through mobile technology
Through MIT App Inventor, Abelson aims to show children how they can use technology to shape their world.
Generating high-quality single photons for quantum computing
New dual-cavity design emits more single photons that can carry quantum information at room temperature.
Building a community for statistics and data science at MIT and beyond
Third annual MIT Statistics and Data Science conference gathers a growing interdisciplinary community of researchers and practitioners.
How to tell whether machine-learning systems are robust enough for the real world
New method quickly detects instances when neural networks make mistakes they shouldn’t.
Wireless movement-tracking system could collect health and behavioral data
In some cases, radio frequency signals may be more useful for caregivers than cameras or other data-collection methods.
Using AI to predict breast cancer and personalize care
MIT/MGH's image-based deep learning model can predict breast cancer up to five years in advance.