Paul McNicholas
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Professor and Canada Research Chair
HH 418
(905) 525 9140 ext. 23419
(905) 522-0935
...

Research Area: Computational Statistics

Research Profile: Computational Statistics
Dr. McNicholas' research focuses on computational statistics, and he is at the cutting edge of international research on mixture model-based clustering and classification. Current research includes work on big data featuring outlying or spurious points, with a focus on classification, clustering, dimension reduction and discriminant analysis. Another important aspect of Dr. McNicholas? current research is work on non-Gaussian mixture models, which present a useful alternative to the Gaussian mixture model. Work on clustering categorical data and data of mixed type is ongoing. Applications of Dr. McNicholas? research are readily found in several fields, including bioinformatics, sensometrics, and psychometrics.

Classification, clustering, computational statistics, data science, machine learning, mixture models

2017/2018
Stats 4I03/6I03
Math 4P06A
Stats 4W03

2016/2017
Math 4P06
Stats 780

2015/2016
Math 4P06
Math 4W03
Stats 4W03
Stats 4M03

Publications available here.

Presentations available here.

Currently Supervising:
Xiongying Deng (Msc Stats)
Michael Gallaugher (PhD Math (Stats))
Regina Kampo (PhD CSE)
Muz Mallo (PhD Math (Stats))
Nkumbuludzi Ndwapi (PhD Math (Stats))
Angelina Pesveski (MSc Stats)
Tyler Roick (PhD CSE)
Peter Tair (PhD CSE)

Past Students:
Martin Blostein (MSc Stats)
Jonathan Earl (MSc Stats)
Samir Korkis (MSc Stats)
Nidhi Patel (MSc Stats)
Paula Murray (PhD Math (Stats))
Amay Cheam (PhD Math (Stats))

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McMaster University - Faculty of Science | Math & Stats