Professor Stuk has had a long history of managing teams in applying diverse techniques to the analysis of a wide range of business and technical situations. His early work at the Georgia Tech Research Institute involved innovative application of evolving technology with state of the art spectral analysis of extensive data for use in pattern detection. This led to the work in his PhD dissertation on man-in-the-loop decision support systems. He directed all aspects of technical support, world wide, for Gould's mini-super computer line, NPL. This included management of the field analysts, home office performance/benchmark analysts, proposal development team, computer center, and trade show support. He reported directly to the president and was the primary technical interface to development. Was a member of the 6 man team that made Gould, GSD a separate division, and he generated the structure for the division. Since leaving Gould he has merged teaching, consulting and research while at Georgia Tech and Emory. This work has involved exploiting new computer technology and applying complex techniques to the analysis of data especially in the area of market response. He has taught and applied techniques including Neural Nets and Fractals to a variety of situations including: customer attrition, marketing response, sales/demand forecasting, credit risk, and voting behavior. He has performed quality and reengineering projects with banks, insurance companies/agencies, and medical offices. Stuk was attracted to Emory to create an innovative quantitative analysis department within the Goizueta Business School. He was tasked with building a program for the next century, including the incorporation of the study and use of technology in the classroom and in business. This included redesign of the curriculum and hiring of faculty. Has been involved in the hiring the entire current Decision, Information, and Analysis faculty at Emory. Stuk's research interests are focused around the application of innovative modeling techniques to real world problems. Recent activity has been application of Synthetic Neural Network to predict consumer behavior. In particular the application of Kohonen or self-organizing maps to Internet preference behavior has been developed.
Dr. Stuk's background in military modeling and analysis and research has provided him with a unique experience and reservoir of techniques to combine for optimal results.
PhD in Applied StatisticsGeorgia Institute of Technology
MSOR in Operations ResearchGeorgia Institute of Technology
MS in Systems AnalysisGeorgia Institute of Technology
BA in MathematicsOakland University
BS in EngineeringOakland University