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.
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