Waldyn Martinez

Associate Professor

Information Systems & Analytics


Academic Background

  • PhD in Applied Statistics, University of Alabama, 2012
  • MS in Applied Statistics, University of Alabama, 2009
  • MBA, University of Alabama, Concentration: Business Analytics & Data Mining, 2006
  • MS Management, Pontificia Universidad Catolica Madre y Maestra, 2004
  • BS Computer Science Engineering, Universidad Tecnologica de Santiago, 2000

Academic & Professional Experience

  • Assistant Vice President, Risk Modeler, J.P. Morgan Chase, Columbus, OH, 2012- 2013
  • Teaching Assistant & Instructor, University of Alabama, 2007 - 2011
  • Assistant Vice President, Market Information Manager, Bank of America, Charlotte, NC, 2006 - 2007

Recent Publications

  • Martinez, W.,  Weese, M., Jones-Farmer, A.: A One-Class Peeling Method for Multivariate Outlier Detection with Applications in Phase I SPC, Quality and Reliability Engineering International, 2020, 36 (4): 1272-1295
  • Weng, B., Martinez, W., Tsai, Y.T., Li, C., Lu, L., Barth, J., Megahed, F. M.: Macroeconomic Indicators can Help Predict the Monthly Closing Price of Major U.S. Indices: Insights from Artificial Intelligence, Time-Series Analysis and Hybrid Models, Applied Soft Computing, 2018, 71, 685-697
  • Weng, B., Wang, X., Lu, L., Martinez, W., Megahed, F. M.: Predicting Short-Term Stock Prices using Ensemble Methods and Online Data Sources, Expert Systems with Applications, 2018, 112, 258-273
  • Weese, M., Martinez, W., Jones-Farmer, A.: On the Selection of the Bandwidth Parameter for the k-Chart, Quality and Reliability Engineering International, 2017, 33 (7): 1527-1547
  • Martinez, W. and Gray, J. B:  Noise Peeling Methods for Improving Boosting Algorithms, Computational Statistics and Data Analysis, 2016, 93: 483-497.
  • Weese, M., Martinez, W.,  Megahed, F., Jones-Farmer, A.: Statistical Learning Methods Applied to Process Monitoring: An Overview and Perspective, Journal of Quality Technology, 2016,  48 (1): 4-24.
  • Martinez, W. and Gray, J. B: The role of margins in the performance of Boosting, Wileys Interdisciplinary Reviews (WIREs) Computational Statistics, 2014, 6: 124-131.

Honors & Awards

  • Outstanding Dissertation Award, University of Alabama, 2014,
  • Jeff Kurkjian Teaching Award, University of Alabama, 2010
  • Excellence in Teaching Award by a Doctoral Student, University of Alabama, 2010
  • Fulbright Scholar, Dominican Republic. Visiting country: United States, 2004


Dr. Waldyn Martinez is an Assistant Professor of Business Analytics at Miami University. He received his Ph.D. and M.S. in Applied Statistics from the University of Alabama in 2012, he holds a B.S. in Computer Science from the Universidad Tecnologica de Santiago, a M.S. in Management from Pontificia Universidad Catolica Madre y Maestra and an M.B.A from the University of Alabama.

Prior to joining the faculty at Miami University, Dr. Martinez held the positions of AVP of Risk Modeling & Analytics at JPMorgan Chase and AVP of Market Information Analytics at Bank of America.

Dr. Martinez' research is focused on the area of Statistical Machine Learning, specifically in the theory and applications of ensemble, hybrid and deep learning algorithms. His research has appeared in the Journal of Computational Statistics and Data Analysis, Journal of Quality Technology, Applied Soft Computing, Expert Systems with Applications, Quality and Reliability Engineering International and WIREs Computational Statistics


  • ISA 291 C 115-25 TR FSB0013
  • ISA 630 A 250-410 TR FSB 2037
Waldyn Martinez

Contact Information

Office Hours

  • TR 11-12


* Accessible version of PDF available upon request.