Research

Research Coming Soon. In the meantime, Download my C.V.

&npsp;

Teaching

Teaching Coming Soon. In the meantime, Download my C.V.

&npsp;

Service

Service Coming Soon. In the meantime, Download my C.V.

&npsp;

Dr. Hayden Wimmer

Dr.Hayden Wimmer

Hayden Wimmer has a Ph.D. from the University of Maryland Baltimore County in Information Systems based in data mining and artificial intelligence applied to financial data. He also holds an M.S. is in Information Systems from UMBC, an M.B.A. from the Pennsylvania State University, and a B.S.in Information Systems from York College of PA.

Prior to academia, he worked in industry for over 10 years in different capacities in Information Technology performing programming, web design and administration, server administration, network configuration, database administration, and of course technical support on all levels. He traveled the world in his professional capacities performing support and integration for a multinational company spending time in various U.S. locations as well as Canada, Mexico, France, Germany, Belgium, and China.

Dr. Wimmer has multiple journal publications related to multi-agent systems, artificial intelligence, data science, and I.S. education; and serves in various editorial capacities including co-editor in chief, board member, and reviewer of various journals and conferences and is a member of the Association of Information Systems. He has taught courses such as programming, database management, project management, I.T. infrastructure, and healthcare informatics. His research is published in top journals such as Decision Support Systems (DSS), Expert Systems with Applications (ESwA), Journal of Computer Information Systems (JCIS), Computers and Geosciences, and Computers in Human Behavior. Dr. Wimmer's research has been funded for over $300,000 with nearly $200,000 from federal support and $24,000 from industry sources.

Download my C.V.

My [DAC] Lab

My Google Scholar Profile

A Promotional Video from Georgia Southern

My cool implementation of Data Stream Mining Based on C4.5