Skip to Main Content

The University of Tennessee

Center for Intelligent Systems and Machine Learning

Frequently Used Tools:


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

  • January 15, 2015 March 4-5 - Big Data Analytics Conference in Oak Ridge

    The 70th Annual Meeting of the ORAU Council of Sponsoring Institutions is only about six weeks away, and it will be here before we know it. We truly hope you will be able to attend the conference MARCH 4-5, 2015 whose theme is: Big Data Analytics: Challenges and Opportunities. Click HERE to register . The deadline for registration and lodging is MONDAY, FEBRUARY 16, 2015. A number of experts and leaders from academia, government, and private industry will discuss effective strategies and emerging trends in key areas of national importance regarding big data. Conference to be very engaging and informative. There is no registration fee to attend the annual meeting. The business session of the meeting shown on the agenda is open to all.

  • December 16, 2014 MATH 619 - Mathematical Methods of Data Science

    Professor V Maroulas and Professor Fernando Schwartz will be running a seminar in the Spring 2015 entitled: "Mathematical Methods of Data Science". The class will meet on Wednesdays at 2:30pm in Ayres 111. The course number is MATH 619. Format: The class is a 1hr credit; students and faculty will present papers and/or their work, and we will also have visitors. The first meeting will be organizational, and will happen on Wednesday 1/7/15.

  • December 15, 2014 Senior Data Analyst - Full Time Opportunity

    Aspire Health is seeking a full time Senior Data Analyst to lead Aspire’s analysis of claims data from Medicare, Medicaid and Commercial health plans as well as all analysis of internal clinical, operational and financial data. Click HERE to see the job description.