Intelligent Systems Group

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Intelligent Systems Group
Emmanuel Fernandez Larry Mazlack Ali Minai
(coordinator) Carla Purdy William Wee
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Faculty Research Interests
Emmanuel Fernandez Stochastic
models, stochastic decision control processes,
intelligent/adaptive algorithms, information
technology. Larry Mazlack Intelligent
databases and information structures, fuzzy
systems, data mining, hybrid intelligent
systems. Ali Minai Self-organizing systems,
computational biology, neural network models of
cognition, artificial life, sensor
networks. Carla Purdy Intelligent sensor data
processing, hybrid intelligent systems,
computational biology. William Wee
Intelligent signal/image processing, analysis
and understanding.
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Research Areas

• Data mining.
• Sensor networks.
• Neural networks.
• Evolutionary algorithms.
• Distributed intelligence.
• Adaptive decision and control.
• Data and sensor fusion.
• Search and optimization.
• Hybrid intelligent systems.
• Intelligent databases and information
  structures.
• Complex adaptive systems.
• Biologically-inspired systems.
• Bioinformatics and computational biology.
• Intelligent signal/image processing, analysis
  and understanding.

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Course Requirements

• All students must satisfy degree program course
  requirements.
• M.S. Students must take at least 3 and Ph.D.
  students at least 4 of
• EECE 636 Intelligent Systems
• EECE 638 Nonlinear and Intelligent Systems
• EECE 642 Digital Image Processing
• EECE 716 Semantic Web
• EECE 728 Information Theory
• EECE 741 Stochastic Decision and Control
• EECE 785 Special topics in Intelligent Knowledge
  Representation
• EECE 841 Advanced Decision Processes
• EECE 844 Probability and Algorithms
• EECE 854 Complex Systems
• EECE 858 Data Mining
• EECE 867 Biomorphic Systems
• EECE 875 Robust Adaptive Control
• EECE 986 Advanced Computer Vision

• CS 731 Distributed AI
• CS 786 Computational Genomics
• CS 821 Pattern Recognition

• CS 621, 624 Mathematical Logic I and II
• CS 633, 634 Artificial Intelligence I and II
• CS 637 Machine Learning
• CS 724 Logic in AI