Wolfgang S. Jank
Room: CIS 1040
Phone: (813) 974-6762
Wolfgang Jank is the Anderson Professor of Global Management in the School of Information Systems and Management. He teaches classes in statistics and data mining in the masters, MBA and Executive MBA programs.
An author of more than 80 refereed articles, Jank's research focuses on the application of statistics and data mining to data-driven problems in marketing, information systems and operations management. He has been published in journals such as the Journal of Forecasting, the INFORMS Journal of Computing, Marketing Science, the Journal of the American Statistical Association, the Journal of the Royal Statistical Society and the Annals of Applied Statistics. He was awarded the best Information Systems Publication in 2008. He has written three books and has presented his work at national and international meetings.
Jank earned a PhD in statistics from the University of Florida and a master's degree in mathematics from the Technical University of Aachen (Germany). Prior to joining the Muma College of Business, he was an associate professor in the Department of Decisions, Operations & Information Technologies, and served as the director of the Center for Complexity in Business at the University of Maryland's Smith School of Business.
- ISM 6930 - Statistical Data Mining
- QMB 3210 - Computational Methods in Business
- QMB 6305 - Management Decision Analysis
- Tafti A, Zotti R, and Jank, W., (2016), “Real-time Diffusion of Information on Twitter
the Financial Markets,” PLOS One.
- Elmaghraby, W, Jank, W, Karaesmen, I, and Zhang S., (2015), “Sales Force Behavior,
Pricing Information and Pricing Decisions,” Manufacturing & Service Operations Management, 17(4), pp. 495-510.
- Ozpolat, Koray, and Jank, W., (2015), “Getting the Most Out of Third Party Trust Seals:
A Randomized Field Study,” Decision Support Systems, 73, pp. 47–56.
- Fan, Y, Foutz, N, James, G and Jank W., (2014), “Functional Response Additive Model
Estimation with Online Virtual Stock Markets,” Annals of Applied Statistics, 8(4), pp.
- Di, Chongzhi, Crainiceanu, C. M. and Jank, W., (2014), “Multilevel Sparse Functional
Principal Component Analysis,” Stat, 3(1), pp. 126–143.
- Associate editor, Data Science and Business Analytics Track at the International Conference on Information Systems, December 2016
- PhD coordinator, 2012-14; member PhD Committee, 2011-14
- Co-director: Muma College of Business Center for Analytics and Creativity, 2014-present
- Member, American Statistical Association