Computer Science and Artificial Intelligence Laboratory (CSAIL)

  • 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.
  • Postdoctoral associate in the Computer Science and Artificial Intelligence Lab (CSAIL) Hamed Pirsiavash has developed a new algorithm that offers significant improvements in parsing video — linearly, no matter the length, with fixed requirement for memory and reaching conclusions in search more efficiently. Read more.
  • Robert D. Blumofe and Charles E. Leiserson were announced today as the winners of the 2013 Association for Computing Machinery’s (ACM) Paris Kanellakis Theory and Practice Award for contributions to robust parallel and distributed computing. The ACM credits Blumofe and Leiserson for developing provably efficient randomized “work-stealing” scheduling algorithms and Cilk, a small but powerful programming-language extension for multithreaded computing. The Kanellakis Award honors specific theoretical accomplishments that significantly affect the practice of computing. Read more.
  • As the director of MIT’s BigData@CSAIL industry initiative, and the co-director of the more research-focused Intel Science and Technology Center (ISTC) for Big Data, EECS professor and CSAIL principal investigator Sam Madden talks with the MIT News Office about the growing complexity of data. From social networks and images to real time financial transactions, Madden talks about the issues (and opportunities) of what to do with this data. Read more.


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