Philippe Boileau

Master’s Student in Biostatistics

University of California, Berkeley

Biography

I am a master’s student in the Graduate Group in Biostatistics at the University of California, Berkeley under the supervision of Professor Sandrine Dudoit. My research interests revolve around the development of unsupervised statistical learning methods and their application to datasets generated by high-throughput biological experiments. I also enjoy creating open-source statistical software in R.

Interests

Exploratory data analysis
High-dimensional statistics
Statistical genomics
Computational biology
Statistical software development

Education

MA in Biostatistics, 2018-present
University of California, Berkeley
BSc in Honours Statistics, 2016-2018
Concordia University

Recent Publications

Exploring High-Dimensional Biological Data with Sparse Contrastive Principal Component Analysis

Motivation: Statistical analyses of high-throughput sequencing data have re-shaped the biological sciences. In spite of myriad …

Philippe Boileau, Nima S. Hejazi, Sandrine Dudoit

PDF Code DOI Preprint

scPCA: A toolbox for sparse contrastive principal component analysis in R

Philippe Boileau, Nima Hejazi, Sandrine Dudoit

PDF DOI

Projects

neatmaps

The neatmaps R package simplifies the exploratory data analysis of multiple network datasets through a combination of heatmaps and consensus clustering.

scPCA

The scPCA R package implements sparse constrastive PCA, a variant of PCA that extracts sparse, stable, interpretable, and relevant signal, given access to control data

Teaching

University of California, Berkeley

Statistical Analysis of Categorical Data, PBHLTH 241 – Graduate Student Instructor (Spring ‘20)
Principles and Techniques of Data Science, DATA 100 – Graduate Student Instructor (Spring ‘19, Fall ‘19)
Introduction to Probability and Statistics in Biology and Public Health, PBHLTH 142 – Graduate Student Instructor (Fall ‘18)

Experience

Graduate Student Intern

Sutter Health - Research, Development and Dissemination

Jun 2019 – Aug 2019 Walnut Creek, CA, United States

Developed a statistical modeling pipeline using electronic health record data to evaluate a patient’s risk of becoming septic during their hopsital visit. The pipeline, relying on data-adaptive ensemble techniques, generated preliminary results demonstrating its superiority over existing methods.

Undergraduate Summer Researcher

Concordia University

May 2017 – Sep 2017 Montreal, QC, Canada

Developed an exploratory data analysis method for high-dimensional network data under the supervision of Dr. Lea Popovic and Dr. Lisa Kakinami. The method was applied to the the Quebec Adipose and Lifestyle Investigation in Youth cohort data to explore potential associations between social networks and lifestyle behaviours related to youth obesity.

Research Assistant

Canadian Longitudinal Study on Aging, Statistical Analysis Center

Jun 2015 – Jul 2018 Montreal, QC, Canada

Worked with biostatisticians, data curators and data access managers on various projects, including the preparation of statistical reports for the Public Health Agency of Canada, the development of an R package to facilitate analysis of proprietary data, the creation of software to verify accuracy of survey responses and the curation of a public use dataset.

Research Assistant

John Abbott College

Dec 2014 – Sep 2015 Sainte-Anne-de-Bellevue, QC, Canada

Created metrics to measure the offensive consistency of hockey players in the National Hockey League under the supervision of Dr. Jonathan Guillemette.