Michael Brusco

Synovus Professor of Business Administration
Michael Brusco
359 RBB
Academic Specialty
Business Analytics

Ph.D., Florida State University, 1990
MBA, Florida State University, 1986
BBA, Florida Atlantic University, 1985
A.A., Broward Community College, 1982

Areas of Expertise

Linear ordering

Dr. Michael Brusco is the Synovus Professor of Business Administration in the Department of Business Analytics, Information Systems and Supply Chain at Florida State University’s College of Business. His academic specialty is operations management, and he teaches courses in the MBA and Master of Science in Business Analytics (MS-BA) programs. His research has been published in Decision SciencesIIE TransactionsJournal of Abnormal PsychologyJournal of MarketingJournal of Marketing ResearchJournal of Mathematical PsychologyJournal of Operations ManagementManagement ScienceMarketing ScienceMultivariate Behavioral ResearchNaval Research LogisticsOperations Research, Psychological Methods, PsychometrikaScienceTechnometrics and other journals. He serves as an associate editor for the British Journal of Mathematical and Statistical Psychology.

He earned his bachelor’s degree in marketing from Florida Atlantic University. His MBA and Ph.D. in business administration are both from Florida State University.

Selected Published Research

Brusco, M. J., Steinley, D., & Watts, A. L. (in press). Disentangling relationships in symptom networks using matrix permutation methods. Psychometrika.
Brusco, M., Davis-Stober, C. P., & Steinley, D. (2021). Ising formulations of some graph-theoretic problems in psychological research: models and methods. Journal of Mathematical Psychology, 102 (June), Article 102536. https://doi.org/10.1016/j.jmp.2021.102536
Steinley, D., & Brusco, M. J. (2021). On fixed marginal distributions and psychometric network models. Multivariate Behavioral Research, 56 (2), 329-335.
Loeffelman, J., Steinley, D., Boness, C. L., Trull, T. J., Wood, P. K., Brusco, M. J., & Sher, K. J. (2021). Combinatorial optimization of classification decisions: An approach to refine psychiatric diagnoses. Multivariate Behavioral Research, 56 (1), 57-69.
Brusco, M. J., Steinley, D., Hoffman, M., Davis-Stober, C., & Wasserman, S. (2019). On Ising models and algorithms for the construction of symptom networks in psychopathology research. Psychological Methods, 24 (6), 735-753.
Hoffman, M., Steinley, D., Gates, K. M., Prinstein, M. J., & Brusco, M. J. (2018). Detecting clusters/communities in social networks. Multivariate Behavioral Research, 53 (1), 57-73.
Brusco, M. J., Shireman, E., & Steinley, D. (2017). A comparison of latent class, K-means, and K-median methods for clustering dichotomous data. Psychological Methods, 22 (3), 563-580.
Steinley, D., Brusco, M. J., & Hubert, L. (2016). The variance of the adjusted Rand index. Psychological Methods, 21 (2), 261-272.
Steinley, D., & Brusco, M. J. (2011). Evaluating mixture-modeling for clustering: Recommendations and cautions. Psychological Methods, 16 (1), 63-79.
Steinley, D., & Brusco, M. J. (2011). Choosing the number of clusters in K-means clustering. Psychological Methods, 16 (3), 271-285.
Brusco, M. J., & Steinley, D. (2010). K-balance partitioning: An exact method with application to generalized structural balance and other psychological contexts. Psychological Methods, 15 (2), 145-157.
Köhn, H.-F., Steinley, D., & Brusco, M. J. (2010). The p-median model as a tool for clustering psychological data. Psychological Methods, 15 (1), 87-95.
Brusco, M. J., & Steinley, D. (2009). Integer programs for one- and two-mode blockmodeling based on prespecified image matrices for structural and regular equivalence. Journal of Mathematical Psychology, 53 (6), 577-585.
Brusco, M. J., & Köhn, H.-F. (2009). Exemplar-based clustering via simulated annealing. Psychometrika, 74 (3), 457-475.
Brusco, M. J., Köhn, H.-F., & Stahl, S. (2008). Heuristic implementation of dynamic programming for matrix permutation problems in combinatorial data analysis. Psychometrika, 73 (3), 503-522.
Brusco, M. J., & Steinley, D. (2007). A comparison of heuristic procedures for minimum within-cluster sums of squares partitioning. Psychometrika, 72 (4), 583-600.
Brusco, M. J. (2006). A repetitive branch-and-bound algorithm for minimum within-cluster sums of squares partitioning. Psychometrika, 71 (2), 347-363.
Brusco, M. J., & Stahl, S. (2005). Optimal least-squares unidimensional scaling: Improved branch-and-bound procedures and a comparison to dynamic programming. Psychometrika, 70 (2), 253-270.
Brusco, M. J. (2004). Clustering binary data in the presence of masking variables. Psychological Methods, 9 (4), 510-523.
Brusco, M. J. (2002). Identifying a reordering of the rows and columns of multiple proximity matrices using multiobjective programming. Journal of Mathematical Psychology, 46 (6), 731-745.
Brusco, M. J. (2002). A branch-and-bound method for fitting anti-Robinson structures to symmetric dissimilarity matrices. Psychometrika, 67 (3), 459-471.
Brusco, M. J., & Cradit, J. D. (2001). A variable selection heuristic for K-means clustering. Psychometrika, 66 (2), 249-270.
Brusco, M. J., & Stahl, S. (2001). An interactive approach to multiobjective combinatorial data analysis. Psychometrika, 66 (1), 5-24.