January 2010

My research  efforts are primarily in the area of Artificial Intelligence (AI), machine learning, and Robotics.  I am also involved in research and development in the related areas of knowledge discovery, data mining, and databases.  I am a founder and member of the Intelligent Systems Lab (ISL) and the Institute for Research on Intelligent Systems (IRIS) project. Our efforts lie in exploration, design, and implementation of autonomous intelligent agents. The institute provides a venue for curriculum development, research, service learning, and outreach.

My experiences in AI span seventeen years and include work in artificial neural networks, ensembles of constructive networks, selection and combination methods, and development of the Neural Network Ensemble Simulator (NNES) and Scientific Database (NNES SciDB). Additionally, I have over twenty years of teaching experience, including: AI, robotics, cognitive science, knowledge engineering, data acquisition, database technologies, software engineering, programming, theory of computation. My related interests encompass machine learning, embodied intelligence, and data mining. Application areas of greatest interest (for collaborative efforts) include autonomous robots for search and rescue, bio-surveillance, threat detection, sustainability, public and foreign policy, environmental/ecological, humanitarian efforts/health&safety.

My doctoral work was in Artificial Neural Networks. I am still very much interested in neural network learning algorithms, architectures, and applications.  My dissertation, entitled Improving Generalization of Constructive Neural Networks Using Ensembles proposed an ensemble of constructive networks and several combination methods for classification. This research was performed under the direction of R.C. (Chris) Lacher, Professor and Chair, Department of Computer Science and completed in the Spring of 1999. 

I have been involved with neural network research since 1993 and am fascinated by the endless possibilities afforded by neuro-computing. The application of neural networks for pattern recognition and classification are of particular interest to me, regardless of the domain.  I have collaborated on multi-agent hybrid intelligent systems, incorporating multiple artificial intelligence technologies, such as neural networks, genetic algorithms, and robotics, for purposes of knowledge discovery, data mining, or knowledge discovery.

During my graduate study at both Florida State University and Western Illinois University, I spent a significant amount of time on the study and implementation of expert systems, hypermedia, and database technologies. In conjunction with my master's thesis, I conducted research in hypertext technology and experimental management systems (EMS). This led to further research combining hypermedia and EMS technologies, as well as hypermedia functionality under an object-oriented database paradigm. Although I am not currently pursuing research in these areas, they continue to interest me and will likely resurface in future work.

Many complex problems exist in our world. The solutions for such problems may be surprisingly simple, or complex themselves. Yet, for many, computational solutions exist at our fingertips. We see examples of this with each passing day: robotic spacecraft, VR surgical techniques, and autonomous vehicle control just to name a few. In order to provide useful tools to solve serious problems we must be continually searching for ways in which to advance existing technologies. Our search must be one of determination and perseverance, for the solution may be just within our grasp. It is in this spirit that I intend to probe uncharted territories, in the search for solutions to real problems. I have a genuine desire to devote my efforts to science. It is the lure of scientific discovery and application to real-world problems that makes the field so exciting. 

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