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.
MATH 523 to be taught FALL 2015
Dr. Vasileios Maroulas will be teaching Math 523 next semester (and Math 524 in the Spring). The series Math 523-4 is the core of any course and research topic related to SDEs, SPDEs, Computational Probability and Statistics, Mathematical Statistics, Data Sciences, and in general is the central topic of a huge list of modern research topics. The course will focus on the foundations of probability illustrated by many examples, and when it is necessary, applications will be mentioned. We will use Rick Durrett’s book on “Probability Theory and Examples” (4th edition).
Announcement of a Defense of a Dissertation
Benjamin Walter Martin, Candidate for a Doctor of Philosophy, Michael W. Berry, Major Professor, July 14, 2015 @ 10:00 AM, Min H. Kao 639,
“Computational Analysis of Neutron Scattering Data” Click HERE to see full announcement
Text Analytics Job Openings
Boeing Research & Technology (BR&T) in Huntsville, AL ~ http://www.boeing.com/careers/ ~ Text analytics job openings: Search by req number of interest : (also Machine learning openings)
1500021021 - TA experienced
1500021026 - TA early career
1500020285 - Knowledge Modeling
- Empirical assissment of route choice impact on emissions over diferent road types, traffic demands, and driving scenarios by
- Queuing delays associated with secondary incidents by
- Exploring traffic data aggregation bias due to the trastion of traffic states by
- A 1 TOPS/W Analog Deep Machine-Learning Engine with Floating-Gate Storage in 0.13 um CMOS by