II - Computer Science (Artificial Intelligence)

SHARE:
  • Using Bayesian regression, Devavrat Shah, member of the Laboratory for Information and Decision Systems and the Computer Science and Artificial Intelligence Lab (LIDS) and recent graduate student Kang Zhang have identified patterns from five months of price data from all major Bitcoin exhanges — enabling them to predict the price of Bitcoin — thereby allowing them to double their investment over a 50 day period. Read more.
  • A team led by Computer Science and Artificial Intelligence Lab (CSAIL) researchers including EECS associate professor Wojciech Matusik and project lead and doctoral candidate Adriana Schulz has developed “Fab By Example,” the first data-driven method to help people design products, with a growing database of templates that allow users to customize thousands of complex items — without the need to understand the mechanical engineering that might normally be expected. The team will be presenting its system at this month’s Siggraph graphics conference. Read more.
  • Researchers at MIT -- including EECS graduate student Abe Davis and EECS faculty members Fredo Durand and Bill Freeman, and members of the Computer Graphics Group in MIT's Computer Science and Artificial Intelligence Lab (CSAIL) have collaborated with colleagues at Microsoft and Adobe to develop an algorithm to reconstruct an audio signal produced by practically invisible vibrations of objects filmed in video and normally inaudible to human hearing. Read more.
  • Light is everything to good photography. Knowing this fact well, EECS professor Fredo Durand, also an experienced photographer, has begun to create a new system that uses drones (light-equipped autonomous robots) to create accurate lighting while communicating with the camera-mounted interface. Durand and several other researchers will report on their work at an upcoming international symposium in August.
  • At the IEEE Conference on Computer Vision and Pattern Recognition this month, EECS faculty member and associate department head William Freeman and colleagues from the Computer Science and Artificial Intelligence Lab (CSAIL) will present a new algorithm that can, with roughly 80 percent accuracy, determine whether a given snippet of video is playing backward or forward. Read more.
  • EECS faculty members Dina Katabi, director of the Wireless Center at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and CSAIL colleague Robert Miller with EECS graduate students Fadel Adib and Zach Kabalec have collaborated to develop wireless technology to track a person's vital signals such as breathing (heart rate) and more from another room with no need for intrusive wearable technologies. Read more.
  • MIT's Computer Science and Artificial Intelligence Lab (CSAIL) held a two day conference celebrating 50 years of computer science looking forward to the future with solutions for today's obstacles and tomorrow's solutions. Read more.
  • Unlike addressing the problem of object detection, a major area of research in computer vision, Prof. Bill Freeman, principal investigator in the Computer Science and Artificial Intelligence Lab (CSAIL) and associate department head in MIT's Electrical Engineering and Computer Science (EECS) Department, has worked with EECS graduate student Andrew Owens and colleagues from the University of Virginia, the Woods Hole Oceanographic Institute and Flyby Media to .... Read more.
  • Prof. Daniela Rus, Director of MIT's Computer Science and Artificial Intelligence Lab (CSAIL) and head of the Distributed Robotics Lab (DRL) envisions new ways for design and manufacture of robots — including the potential for one robot per child in schools. She and members from the DRL group received multiple prizes at the Ultra-Affordable Robot competition particularly for the group's printable, origami-inspired Segway robot, called SEG, which won first place.

Pages

Subscribe to II - Computer Science (Artificial Intelligence)