David Enke is currently a Curators’ Distinguished Teaching Professor and Interim Department Chair of Engineering Management and Systems Engineering (EMSE) at the Missouri University of Science and Technology (Missouri S&T, formally UMR, the University of Missouri - Rolla). Professor Enke received his PhD in Engineering Management in 1997, his MS in Engineering Management in 1994, and his BS in Electrical Engineering in 1990, all from UMR. Prior to returning to Missouri S&T as Professor and Chair of the EMSE department in the spring of 2012, Professor Enke was the H. Michael and Laurie Krimbill Faculty Fellow of Finance and Chair of the Department of Finance & Operations Management 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 the McDonnell Douglas Corporation (now The Boeing Company) prior to his graduate studies.

Professor Enke is the founder of the Laboratory for Investment and Financial Engineering (LIFE) at Missouri S&T and is a member of the Missouri S&T Intelligent Systems Center. He is an active reviewer for multiple finance and computational intelligence journals, is an area editor for the journal The Engineering Economist (topics: AI, machine learning, computational intelligence, data analytics) and was a past Co-Chair of the Artificial Neural Networks in Engineering conference. Professor Enke (Google Scholar, Scopus) has published over 115 journal publications, book chapters, and conference proceedings, and has been a part of research teams that have secured external funding from industry and government agencies. He has been the recipient of 8 research paper awards and 12 outstanding teaching awards.

Professor Enke has teaching interests in the areas of investments, derivatives, financial engineering, financial risk management, 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, and developing adaptive trading systems using computational intelligence, such as artificial neural networks, fuzzy logic, and evolutionary systems. Data analytics research also includes exploring the use of machine learning and computational intelligence for the analysis of large healthcare datasets. In addition to financial data analytics, Professor Enke also has interest in fintech, including using artificial intelligence, blockchain technology, smart contracts, and decentralized finance for facilitating financial transactions. Professor Enke has published his research findings in Expert Systems with Applications, The Engineering Economist, Neurocomputing, Financial Innovation, Applied Soft Computing, the International Journal of General Systems, the Journal of Smart Engineering Systems Design, the Journal of Power and Energy Systems, the International Society of Pharmaceutical Engineering, the Engineering Management Journal, and the Global Journal of Business Research.


Last Updated 9/21/22