Associate Member, Department of Computing and Software, McMaster University.
Director, MacDATA Institute, McMaster University.
Canada Research Chair in Computational Statistics (Tier 1).
Research focusing on computational statistics, data science and machine learning, especially mixture model-based clustering and classification.
Current research includes work on non-Gaussian mixtures, matrix variate distributions, and real problems in big data analytics.
Research group currently comprises a PDF, six Ph.D. students, five Master's students, and two undergraduate researchers.
New monograph Data Science with Julia published by Chapman & Hall/CRC Press.
Research monograph Mixture Model-Based Classification published by Chapman & Hall/CRC Press.
Selected Recent Open Access publications
Silva, A.; Rothstein, S.J.; McNicholas, P.D. and Subedi, S. (2019), 'A multivariate Poisson-log normal mixture model for clustering transcriptome sequencing data’, BMC Bioinformatics 20:394. [doi]
McNicholas, P.D. (2019), 'Data science', FACETS 4(1), 131-135. [doi]
Prospective students are welcome to send an email but, due to the volume received, the vast majority will not receive a response.
Department of Mathematics & Statistics,
McMaster University, 1280 Main St. W., Hamilton, ON L8S 4K1.
t: +1-905-525-9140, x 23419 e: mcnicholas [at] math.mcmaster [dot] ca