Our vision is data-driven machine learning systems that advance the quality of healthcare, the understanding of cyber arms races and the delivery of online education.
We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.
EQ-Radio can infer a person’s emotions using wireless signals. It transmits an RF signal and analyzes its reflections off a person’s body to recognize his emotional state (happy, sad, etc.).
The creation of low-power circuits capable of speech recognition and speaker verification will enable spoken interaction on a wide variety of devices in the era of Internet of Things.
We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.
This week it was announced that MIT professors and CSAIL principal investigators Shafi Goldwasser, Silvio Micali, Ronald Rivest, and former MIT professor Adi Shamir won this year’s BBVA Foundation Frontiers of Knowledge Awards in the Information and Communication Technologies category for their work in cryptography.
When a power company wants to build a new wind farm, it generally hires a consultant to make wind speed measurements at the proposed site for eight to 12 months. Those measurements are correlated with historical data and used to assess the site’s power-generation capacity.This month CSAIL researchers will present a new statistical technique that yields better wind-speed predictions than existing techniques do — even when it uses only three months’ worth of data. That could save power companies time and money, particularly in the evaluation of sites for offshore wind farms, where maintaining measurement stations is particularly costly.