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The University of Tennessee

Center for Intelligent Systems and Machine Learning

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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.

Recent News

  • October 29, 2014 COSC 526 (Data Mining) Offering for Spring 2015

    Dr. Arvind Ramanathan, CISML ORNL Faculty Affiliate and EECS Joint Faculty, will be offering a section of COSC 526 (Data Mining) for Spring Semester 2015. The emphasis of this section will be on "Big Data" and will be held on Tu/Th at 5:05pm. Tentative topics to be covered include: (1) Introduction to big data mining paradigms using (a) Distributed computing tools such as Map-Reduce/Hadoop and (b) Multi-core tools including GPUs and heterogeneous compute resources, (2) Ideas to "munge, manipulate and analyze" large volumes of data, (3) Streaming Data Analytics, (4) Randomized/probabilistic approaches to construct matrix decompositions/ dimensionality reduction, (5) Similarity search in high dimensional datasets, (6) Link Detection/ Page Rank and applications, and (7) Graph mining techniques.

    Planned datasets for course projects include: (1) large volumes of social media data (over a year worth of data collected at ORNL; >10 TB), (2) open source claims data from the Centers for Medicaid and Medicare (~80-100 GB but complex and noisy healthcare related data), (3) 1000 genome project ( >2 TB data but highly complex and noisy biological datasets), and (4) cybersecurity data.

    The course grade will be based on three mini-projects (with mini implementation examples), a course-project (which begins within the first two weeks of class) and a final poster session. For more information about the course, please contact Dr. Ramanathan (ramanathana [at] ornl [dot] gov).

  • October 29, 2014 Ye Sun, Candidate for a Master of Science

    Announcement of a Defense of a Dissertation: ““Nonnegative Matrix Factorization on Vehicle Crash Summaries” Friday, October 31, 2014 at 2:00 P.M. ~ Min H. Kao 354 ~ Dr. Michael W. Berry, Major Professor Click HERE to see full annoucement

  • October 22, 2014 Chad Steed receives Early-Career Researcher

    This award is part of 2014 ORNL Honors and Awards Honorees ~ Dr. Steed is a CISML - ORNL Affiliate . The award is for early-career success in the study of visual analytics as demonstrated by high-impact publications, prestigious awards, exceptional community service, broad multidisciplinary collaborations, and steadfast dedication to the scientific mission of the Laboratory. Click HERE for more info on honors and awards