معرفی
Dr. Michael Gallaugher is an Assistant Professor of Statistical Science at Baylor University. He holds a Ph.D., M.S., and B.S. in Statistics from McMaster University. His research focuses on clustering and classification methodologies, particularly in matrix/tensor variate data, mixed-type data, clickstream analysis, and outlier detection. He has been recognized with prestigious awards including the Vanier Canada Graduate Scholarship and the Banting Postdoctoral Fellowship.
Education:
- Ph.D., Statistics, McMaster University (2020)
- M.S., Statistics, McMaster University (2017)
- B.S., Statistics, McMaster University (2015)
Research Interests:
Dr. Gallaugher's work emphasizes advanced clustering techniques for complex data structures, including high-dimensional datasets, clickstream behavior analysis, and skewed distribution modeling. His contributions span statistical methodology development and applications in fields like bioinformatics and sports science. His recent work explores hidden Markov models for time series and robust co-clustering algorithms.
Publications Trends:
His publications reflect a strong focus on matrix-variate distributions, skewed data modeling, and algorithmic innovation in clustering. Recent work (2022-2025) highlights advancements in contaminated normal mixtures, co-clustering for high-dimensional data, and spatial regression models.
Awards:
- Vanier Canada Graduate Scholarship
- Banting Postdoctoral Fellowship
Advising & Grants:
While no advisees are listed, his research has been supported by grants from the Natural Sciences and Engineering Research Council of Canada. He contributes to statistical consulting services at Baylor and collaborates internationally on methodological projects.
Labs & Teams:
He is affiliated with Baylor's Department of Statistical Science and collaborates with research groups focused on machine learning and statistical computing.
