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.
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.
Active Grants
Center for Durable and Resilient Transportation Infrastructure (DuRe-Transp), University Transportation Center (UTC) – University of TX at Arlington lead, Department of Transportation, co-PI, $570,000, 2/2023 to 5/2029.
Active Projects
Deep Learning for Bitcoin Price Direction Prediction: An Empirical Comparison of Models and Trading Strategies, with Oluwadamilare Omole, Systems Engineering PhD student.
Bitcoin Price Direction Prediction Using On-chain Data, with Ritwik Dubey, Engineering Management PhD student.
Machine Learning Maintenance Cost Forecasts for Better Infrastructure LCCA (funded by UTC/DOT), with Shahla Shrinzad, Systems Engineering PhD student.