Peer-Reviewed Articles (Published and Accepted)

[1] Franczak, B.C., Browne, R.P., McNicholas, P. D., and Findlay, C.J. (2015), `Product selection for liking studies: the sensory informed design'. Food Quality and Preference. 44, 36-43. [doi]

[2] Franczak, B.C., Tortora, C., Browne, R.P., and McNicholas, P. D. (2015), `Unsupervised learning via mixtures of skewed distributions with hypercube contours'. Pattern Recognition Letters. 58(1), 69-76. [doi]

[3] Franczak, B.C., Browne, R.P., and McNicholas, P.D. (2014), `Mixtures of shifted asymmetric Laplace distributions'. IEEE Transactions in Pattern Analysis and Machine Intelligence. 36(6), 1149-1157. [doi]

Peer-Reviewed Articles (Submitted)

[4] Franczak, B.C., Browne, R.P., McNicholas, P.D., Findlay, C.J., and Castura, J. `A comparison of ten imputation procedures for central location test trials'. Journal of Sensory Studies. Submited Jan. 2015. Revised and Resubmitted Nov. 2015.

[5] Tortora, C., Browne, R.P., Franczak, B.C., and McNicholas, P.D. `A mixtures of coalesced generalized hyperbolic distributions'. Journal of Classifcation. Submitted Dec. 2014.

Preprints

[6] Franczak, B.C., Browne, R.P., and McNicholas, P.D., `Parsimonious shifted asymmetric Laplace mixtures'. arXiv:1311.0317

Software

[7] Tortora, C., Browne, R.P., Franczak, B.C., and McNicholas, P.D. (2014), MixGHD: Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions, R package v1.3.

[8] Franczak, B.C., Browne, R. P., and McNicholas, P.D. (2014), sensory: Simultaneous Model-Based Clustering and Imputation via a Progressive Expectation-Maximization (PEM) algorithm. R package v1.0.

Other

[9] Franczak, B.C., ‘Mixtures of shifted asymmetric Laplace distributions’, PhD Thesis. Department of Mathematics and Statistics, University of Guelph, March 2014.

Presentations (Oral)

i. Parsimonious Multiple Scaled Mixtures. Conference of the International Federation of Classification Soceities. Bologna, Italy. July 2015.

ii. Mixtures of skewed distributions with hypercube contours. The 5th International Conference of the ERCIM Working Group on Computation and Methodological Statistics. Pisa, Italy. Dec. 2014. Invited

iii. Model-based clustering and classification via mixtures of shifted asymmetric Laplace (SAL) distributions. The 1st Annual Southwestern Ontario Graduate Mathematics Conference. Guelph, Ontario, Canada. June 2013.

iv. Clustering and Classification of Asymmetric Data. The 41st Annual Meeting of the Statistical Society of Canada. Edmonton, Alberta, Canada. May 2013.

v. Model-based clustering and classification via mixtures of shifted asymmetric Laplace (SAL) distributions. The 7th International Conference of the ERCIM Working Group on Computing and Statistics. Oviedo, Spain. Dec. 2012. Invited

vi. The ParSAL Family. Classification Society Annual Meeting. Pittsburgh, Pennsylvania. June 2012.

vii. The ParSAL Family of Mixture Models. The 40th Annual Meeting of the Statistical Society of Canada.. Guelph, Ontario, Canada. June 2012.

viii. Model Based Clustering Using Mixtures of Asymmetric Laplace Distributions. The 8th International Meeting of the Classification and Data Analysis Group (CLADAG). Pavia, Italy. Sept. 2011.

ix. Model-based Clustering Using Mixtures of Asymmetric Laplace Distributions. The 39th Annual Meeting of the Statistical Society of Canada. Wolfville, Nova Scotia, Canada. June 2011.

Workshops

x. Imputation of Data for Preference Segmentation in Incomplete Designs. The 12th Sensometrics Conference. Chicago, Illinois, USA. July 2014.

Seminars

xi. Mixtures of Skewed Distributions with Hypercube Contours. Statistics Seminar. McMaster University. Dec. 2014. Invited

xii. Model-based clustering and classification using mixtures of shifted asymmetric Laplace distributions. Computational Statistics Seminar. University of Guelph. Oct. 2011. Invited

Presentations (Poster)

xiii. Meta-attributes in sensory descriptive analysis. The 11th Pangborn Sensory Science Symposium. Gothenburg, Sweden. Aug. 2015.

xiv. A Markov Model for Temporal Dominance of Sensations (TDS) data. The 11th Pangborn Sensory Science Symposium. Gothenburg, Sweden. Aug. 2015.

xv. Cluster-Wise Imputation via the EM Algorithm. The 12th Sensometrics Conference. Chicago, Illinois, USA. July 2014.

xvi. The ParSAL Family of Mixture Models for Model-Based Clustering and Classification. Working Group in Model-Based Clustering. Guelph, Ontario, Canada. June 2012.

xvii. Model-based Clustering Using Mixtures of Gamma Distributions. The 38th Annual Meeting of the Statistical Society of Canada. Quebec City, Quebec, Canada. May 2010.

Academic Service

Secretary and Treasurer, North American Classification Society. Jan. 2016 - Dec. 2017

Volunteer, May at Mac 2015

Organizing Committee, Classification Society Annual Meeting. McMaster University. Winter - Summer 2015

General Director, Graduate Student Association. University of Guelph. Fall 2013 - Winter 2014

Volunteer, 40th Annual Meeting of the Statistical Society of Canada. University of Guelph. June 2012

Referee Service

Computational Statistics & Data Analysis

Advances in Data Analysis and Classification

Journal of Canadian Statistics