Maria Weese

Associate Professor

Information Systems & Analytics


Academic Background

  • Ph.D. University of Tennessee, Statistics, 2010
  • M.S. University of Tennessee, Statistics, 2006
  • B.A. Virginia Tech, Chemical Engineering, 2001

Academic & Professional Experience

  • Associate Professor, Department of Information Systems & Analytics, Miami University (Aug. 2020-present)
  • Affiliate Faculty Member, Department of Statistics, Miami University (May 2019-present)
  • Richard T. Farmer Assistant Professor, Department of Information Systems & Analytics, Miami University (Aug. 2018-July 2020)
  • Assistant Professor, Department of Information Systems & Analytics, Miami University (Aug. 2014-July 2018)
  • Lecturer, Department of Information Systems & Analytics, Miami University (Aug. 2012- July 2014)
  • Visiting Assistant Professor, Department of Decision Sciences and Management Information Systems, Miami University (Aug. 2010-July 2012)
  • Statistical Consultant, Statistical Consulting Center, University of Tennessee (2004-2006)
  • Process Improvement Engineer II, Celanese Acetate (2001-2004)

Recent Publications

  • Lee, L., Weese, M.L., Martinez, W.G., Jones-Farmer, L.A., Robustness of the One-Class Peeling Method to the Gaussian Kernel Bandwidth. In Press: Quality and Reliability Engineering International
  • Weese, M.L., Stallrich, J.W., Smucker, B.J., Edwards, D.J., Strategies for Supersaturated Screening: Group Orthogonal and Var(s ) Designs. In Press: Technometrics
  • Martinez, M.G., Weese, M.L., Jones-Farmer, L.A., A One Class Peeling method for multivariate outlier detection with application to Phase I Monitoring. (2020) Quality and Reliability Engineering International. 36(4):1272:1295
  • Smucker, B.J., Edwards, D.J., Weese, M.L., Response Surface Models: To Reduce or Not to Reduce?. In Press: Journal of Quality Technology.
  • Weese, M.L., Montgomery, D.J., Ramsey,P.J., (2017) Analyzing Definitive Screening Designs: Screening vs. Prediction. Applied Stochastic Models in Business and Industry. 34(2):244-255.
  • Ockuly, R. A., Weese, M.L., Smucker, B.J., Edwards, D.J., Chang, L. (2017) ``Response Surface Experiments: A Meta-Analysis`` Chemometrics and Intelligent Laboratory Systems. 164, 64-75.
  • Weese, M. L., Smucker, B. J., Edwards, D. J., (2017) "\A Criteria for Constructing Powerful Supersaturated Designs when Effect Directions are Known". Journal of Quality Technology. 49(3):265-277.

Honors & Awards

  • 2021: Center for Analytics and Data Science Faculty Fellow
  • 2017: Nominee for Outstanding Professor
  • 2014: Nominee for Outstanding Professor
  • 2014 Best Presentation Honorable Mention, Joint Statistical Meetings

Professional Interests

  • Research: Analysis based Design, Data Stream Monitoring, Screening Design, Optimal Supersaturated Design


Dr. Maria Weese earned a bachelors degree in Chemical Engineering from Virginia Tech and worked for three years as a Process Improvement Engineer for Celanese Acetate before returning to graduate school to pursue graduate studies in Statistics at the University of Tennessee. Maria is an active researcher in the areas of design of statistical experiments and statistical monitoring. As such she has high quality publications in both of those areas. Dr. Weese has been in the Farmer School of Business Miami University since receiving her PhD in 2010 and has taught extensively in the Business Analytics program developing the current Business Analytics Practicum course as well as Statistical Monitoring and Design of Experiments and Introduction to Data Mining.


  • ISA 365
  • A 1005-1125 TR FSB 0013
  • B 1140-1 TR FSB 0013
  • ISA 633 A 830-950 TR FSB 0013
Maria Weese

Contact Information

Office Hours

  • M 1-3
  • W 10-NOON


* Accessible version of PDF available upon request.