Fadel Adib joins Media Lab faculty
Adib is directing a new research group at the Media Lab, aiming to uncover, analyze, and engineer natural and human-made networks.
Adib is directing a new research group at the Media Lab, aiming to uncover, analyze, and engineer natural and human-made networks.
Given a still image, CSAIL deep-learning system generates videos that predict what will happen next in a scene.
Developed at Computer Science and Artificial Intelligence Laboratory, “MoVR” system allows VR headsets to communicate without a cord
Ali Jadbabaie seeks to optimize large-scale systems, from social networks to teams of people or devices.
New training technique would reveal the basis for machine-learning systems’ decisions.
MegaMIMO system from the Computer Science and Artificial Intelligence Lab speeds data transfer by coordinating multiple routers at the same time.
New design should enable much more flexible traffic management, without sacrificing speed.
Analysis of ant colony behavior could yield better algorithms for network communication.
Batches of shoebox-sized satellites could improve estimates of Earth’s reflected energy.
Network can protect users’ anonymity if all but one of its servers are compromised.
New book by Senseable City Lab researchers presents vision of data-driven urban design.
Deep-learning vision system from the Computer Science and Artificial Intelligence Lab anticipates human interactions using videos of TV shows.
Video-trained system from MIT’s Computer Science and Artificial Intelligence Lab could help robots understand how objects interact with the world.
Bringing together engineers, data theorists, mathematicians, economists, biologists, and policy experts, IDSS is looking at financial risk through a multidisciplinary lens.