Intelligent Systems Research

Intelligent

Systems

Group


Emmanuel Fernandez

Larry Mazlack

Ali Minai (coordinator)

Carla Purdy

William Wee

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.

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.

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 621, 624 Mathematical Logic I and II

•

CS 633, 634 Artificial Intelligence I and II

•

CS 637 Machine Learning

•

CS 724 Logic in AI

•

CS 731 Distributed AI

•

CS 786 Computational Genomics

•

CS 821 Pattern Recognition