Gary Weckman, Ph.D.

Dr. Weckman has an extensive research background in data analysis, with specific training and expertise in key research areas of nonlinear modeling. He has authored or co-authored more than 70 peer-reviewed articles in journals and conferences. He has industrial engineering experience with more than 12 years at such firms as General Electric Aircraft Engines and 17 years in academic research. Currently, he has been researching multidisciplinary applications utilizing knowledge extraction techniques with artificial neural networks (ANN). Dr. Weckman has extensive experience in and possesses an internationally renowned reputation for neural network modeling of complex information systems, both traditional (e.g. applied applications of reliability analysis and telecommunications) and nontraditional (e.g. network modeling applications for financial and ecological monitoring). He has worked on several topics concerning model development for the Saginaw Bay HydroMet database, Grey Box methodology for Sarasota and Saginaw Bays, and technique modeling in modeling harmful algal blooms. His research is directed to the development, validation, and refining of computationally intensive technologies for extracting user-friendly rules in developing a more usable prediction tool and enhance the understanding of ecological systems.