The Center for Intelligent Systems and Machine Learning (CISML) is a collaboration of faculty from three colleges and eight academic departments at the University of Tennessee (UT), and is part of the College of Engineering on the Knoxville campus. Beginning as a simple faculty initiative to create a unified curricula, CISML evolved (in October 2010) into an official UT research center that studies the theory and application of intelligent systems and machine learning. In addition to UT faculty, the Center's research staff is comprised of eight experts from Oak Ridge National Laboratory (ORNL).
CISML's focus is on designing computer-based systems that exhibit intelligent behavior, operate autonomously, and adapt to environmental changes. Examples of the diverse research activities in this area include pattern recognition, robotics, artificial intelligence, biologically-inspired cognitive architectures, bioinformatics, and data mining, to name a few.
CISML 2015 Summer Internships / Research
Click HERE to read an article about the CISML 2015 Summer Internships/Research.
Video of Dr. Michael W. Berry ~ Keynote Speaker in Malaysia
Video highlight ~ https://www.youtube.com/watch?v=qWUqB9V5SPg ~ Dr. Michael W. Berry was the Keynote Speaker at the International Conference Soft Computing in Data Science and Statistics in Science, Business and Engineering held at Pullman Hotel Putrajaya, Malaysia on 2nd - 3rd September 2015.
College's Distinguished Lecture Series
You are invited to hear Dr. James McLurkin ~ Assistant Professor of Computer Science, Rice University ~ October 5, 2015 ~Lecture ~ 4:00-5:00pm ~ 622 Min Kao ~ The Future of Robotics is Swarms: Why a thousand robots are better than one ~ Abstract: Multi-robot systems are the future of a futuristic field. Large populations of robots can solve many practical applications faster, cheaper, and in fundamentally different ways than individual robots. The key to realize this potential are distributed algorithms, and a whole lot of really cheap little robots. These ideas aren't new, ants and bees have been using this approach for 120 million years, and we can learn much from them. Key ideas are illustrated with a live 12-robot demo. bio: http://www.cs.rice.edu/~jm23/
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