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

2016/2017
Math 4P06
Stats 780

2015/2016
Math 4P06
Math 4W03
Stats 4M03/6M03
Stats 4W03
Stats 743

2014/2015
Stats 758

Publications available here.

Presentations available here.

Currently Supervising:
Katharine Clark (MSc Stats)
Michael Gallaugher (PhD Stats)
Milena Hadzi-Tosev (MSc Stats) 
Regina Kampo (PhD Stats)
Sherry Luo (MSc Stats) 
Forrest Paton (PhD Stats) 
Nikola Pocuca (MSc Stats) 
Tyler Roick (PhD CSE)
Peter Tait (PhD Stats)
Xi Zhang (MSc Stats) 

Past Students:
Martin Blostein (MSc Stats)
Amay Cheam (PhD Math (Stats))
Xiongying Deng (Msc Stats)
Jonathan Earl (MSc Stats)
Samir Korkis (MSc Stats)
Muz Mallo (PhD Math (Stats))
Paula Murray (PhD Math (Stats))
Nkumbuludzi Ndwapi (PhD Math (Stats))
Nidhi Patel (MSc Stats)
Angelina Pesveski (MSc Stats)


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McMaster University - Faculty of Science | Math & Stats