About David Enke

Education

  • University of Missouri - Rolla, Doctor of Philosophy, 1997

David Enke

Professor
Engineering Mgt & Sys Engr
221 Engineering Management

573-341-4749 | enke@mst.edu

Education

  • University of Missouri - Rolla, Doctor of Philosophy, 1997

Biography

David Enke received his Ph.D. in Engineering Management in 1997, his M.S. in Engineering Management in 1994, and his B.S. in Electrical Engineering in 1990, all from the Missouri University of Science and Technology (formally the University of Missouri - Rolla). Prior to returning to Missouri S&T as Professor and Chair of Engineering Management and Systems Engineering (EMSE) in the spring of 2012, Professor Enke was an Associate Professor and the H. Michael and Laurie Krimbill Faculty Fellow of Finance at The University of Tulsa. He was previously on the faculty of Missouri S&T from 2000 to 2007 as an Assistant/Associate Professor within the EMSE department. He joined the faculty of Binghamton University in 1999, and was on the faculty at the University of Michigan - Dearborn during 1998. He was employed for six years by McDonnell Douglas Corporation prior to his graduate studies.
Professor Enke is currently an editorial board member for the journal The Engineering Economist, and was a past Co-Chair of the Artificial Neural Networks in Engineering conference. Professor Enke has published over 100 journal publications, book chapters, and conference proceedings, and has been a part of research teams that have secured over $2.6 million in external funding from industry and government agencies. He has been the recipient of 8 best paper awards and 12 outstanding teaching awards. He is currently a Full Professor of Engineering Management and Systems Engineering at Missouri S&T.

Professor Enke has teaching interests in the areas of investments, derivatives, financial engineering, financial risk management, engineering economics, and student investment funds. His primary research interests are in the areas of equity price and volatility forecasting, using options and futures for hedging, and financial modeling, as well as hedge fund replication, endowment investing, and developing adaptive trading systems using computational intelligence, such as artificial neural networks, fuzzy logic, and evolutionary systems. Professor Enke has published his research findings in Expert Systems with Applications, Neurocomputing, The Engineering Economist, the International Journal of General Systems, the Journal of Smart Engineering Systems Design, Journal of Power and Energy Systems, the International Society of Pharmaceutical Engineering, the Engineering Management Journal, and the Global Journal of Business Research.

Course information