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MattMcLeanCV.html
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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Mathew W. McLean</title>
<link rel="stylesheet" href="css/cv.css" type="text/css" />
</head>
<body>
<section>
<div class = "cvHeader">
<div style = "position: relative; float: left;">
<p>Email: mathew [dot] w [dot] mclean [at] gmail [dot] com</p>
<p>Website: <a href="http://mwmclean.github.io" target="blank_">
http://mwmclean.github.io</a></p>
</div>
<div id ="header-right" style = "text-align: right">
<p>Phone: +61 4 5238 9372</p>
<p>Citizenship: Canadian</p>
</div>
</div>
</section>
<hr class = "hr-inner">
<section>
<h1>Education</h1>
<ul>
<li><p>Ph.D. in Operations Research, Cornell University, 2013</p>
<ul>
<li><p>Concentration: Applied Probability and Statistics</p></li>
<li><p>Advisors: David Ruppert and Giles Hooker</p></li>
<li><p>Dissertation: On Generalized Additive Models for Regression with Functional Data</p></li>
</ul></li>
<li><p>M.S. in Operations Research, Cornell University, 2013</p></li>
<li><p>B.Sc. (Hons.) in Statistics, University of Manitoba, 2008</p></li>
</ul>
</section>
<section>
<h1>Professional Experience</h1>
<ul>
<li>
<p>Data Scientist, Displayr, 2017-2024</p>
<ul>
<li><p> Developed and tested features (mostly written in R and
JavaScript) for our market research software products, Q and
Displayr, to simplify and automate data cleaning, analysis,
visualization, and reporting. Since joining, the
company has grown from 20 to 100+ employees and nearly \$14 million
in ARR. </li></p>
<li><p> Setup CircleCI pipelines and an orb for continuous integration
and deploying of R packages to Azure blog storage, achieving 5x
reduction in build times. </li></p>
<li><p> Developed novel algorithm for classifying open-ended text
survey responses involving Google's Universal Sentence Encoder, clustering, and
random forests. Later explored prompt engineering using ChatGPT
for this task and compared with our existing algorithm. </li></p>
<li><p> Maintained/co-authored a
suite of $40+$ R packages for statistical modeling, visualization,
data cleaning and integrating with various web APIs. </li></p>
<li><p> Lead a small team of data scientists to write efficient,
intuitive tools for performing text analysis, driver analysis,
regression, and choice modeling using Scrum. </li></p>
<li><p> Designed user interface as well as interactive visualization
and HTML widget output for data science and machine learning
features in our apps, Displayr and Q. </li></p>
<li><p> Developed models implemented in stan and R for Hierarchical
Bayes choice modeling, simulation, and experimental design. </li></p>
<li><p> Wrote blog posts detailing usage of new features and replied
to customer questions.</li></p>
</ul>
</li>
<li>
<p>Postdoctoral researcher, University of Technology Sydney, 2015-2017</p>
<ul>
<li><p>Supervisor: Matt P. Wand</p></li>
</ul>
</li>
<li>
<p>Postdoctoral researcher, Texas A&M University, 2013-2015</p>
<ul>
<li><p>Supervisor: Raymond J. Carroll</p></li>
</ul>
</li>
</ul>
</section>
<section>
<h1>Publications</h1>
<p><cite>
<span class="me">M. W. McLean</span> and M. P. Wand.
“Variational Message Passing for Elaborate Response
Regression Models”.
In: <em>Bayesian Analysis</em> 14.2 (Jun. 2019), pp. 371-398.</cite></p>
<p><cite>
K. Triff, <span class = "me">M. W. McLean</span>, E. Callaway, et al.
“Dietary fat and fiber interact to uniquely modify global
histone post-translational epigenetic programming in
a rat colon cancer progression model”.
In: <em>International Journal of Cancer</em> 143.6 (May 2018), pp. 1402-1415.</cite></p>
<p><cite><span class = "me">M. W. McLean</span> (2017).
“RefManageR: Import and Manage BibTeX and BibLaTeX References in
R”. <em> The Journal of Open Source
Software</em>. DOI: <a href="http://dx.doi.org/10.21105/joss.00338">10.21105/joss.00338</a>.
R Package also accepted
by <a href="http://ropensci.org"><em>ROpenSci</em></a>.
</cite></p>
<p><cite>
K. Triff, <span class = "me">M. W. McLean</span>, K. Kranti, et al.
“Assessment of Histone Tail Modifications and
Transcriptional Profiling During Colon Cancer
Progression Reveals a Global Decrease in H3K4me3
Activity”.
In: <em>BBA - Molecular Basis of Disease</em> 1863.6 (Jun. 2017), pp. 1392–1402.
DOI: <a href="http://dx.doi.org/10.1016/j.bbadis.2017.03.009">10.1016/j.bbadis.2017.03.009</a>.
</cite></p>
<p><cite>
<span class = "me">M. W. McLean</span>, G. Hooker and D. Ruppert.
“Restricted Likelihood Ratio Tests for Linearity in Scalar-on-Function Regression”.
In: <em>Statistics and Computing</em> 25.5 (Sep. 2015), pp. 997–1008.
DOI: <a href="http://dx.doi.org/10.1007/s11222-014-9473-1">10.1007/s11222-014-9473-1</a>.
arXiv: <a href="http://arxiv.org/abs/1310.5811">1310.5811 [stat.ME]</a>.</cite></p>
<p><cite><span class = "me">M. W. McLean</span>, G. Hooker,
A. M. Staicu, F. Scheipl and D. Ruppert. “Functional
Generalized Additive Models”. In: <EM>Journal of Computational
and Graphical Statistics</EM> 23.1 (Feb. 2014), pp. 249–269.
DOI: <a href="http://dx.doi.org/10.1080/10618600.2012.729985">10.1080/10618600.2012.729985</a>.</cite></p>
<p><cite>Matteson, D. S, <span class = "me">M. W. McLean</span>,
D. B. Woodard and S. G. Henderson. “Forecasting
Emergency Medical Service Call Arrival Rates”. In: <EM>Annals
of Applied Statistics</EM> 5.2B (Jun. 2011), pp. 1379–1406.
DOI: <a href="http://dx.doi.org/10.1214/10-AOAS442">10.1214/10-AOAS442</a>.
arXiv: <a href="http://arxiv.org/abs/1107.4919">1107.4919
[stat.AP]</a>.</cite></p>
</section>
<section>
<h1>Manuscripts</h1>
<p><cite>
<span class="me">M. W. McLean</span>, C. J. Oates and M. P. Wand.
“Real-Time Semiparametric Regression via Sequential Monte
Carlo”.
(2017).
Submitted.</cite></p>
<p><cite><span class = "me">M. W. McLean</span>, F. Scheipl, G. Hooker, S. Greven and D. Ruppert
(2017).
<EM>Bayesian Functional Generalized Additive Models with Sparsely Observed Covariates</EM>.
arXiv: <a href="http://arxiv.org/abs/1305.3585">1305.3585 [stat.ME]</a>.
</cite></p>
<p><cite><span class = "me">M. W. McLean</span>
(2014).
<EM>Straightforward Bibliography Management in R Using the RefManageR Package</EM>.
arXiv: <a href="http://arxiv.org/abs/1403.2036">1403.2036 [cs.DL]</a>.
</cite></p>
</section>
<section>
<h1>Computing Proficiency</h1>
<ul>
<li><p>R (including tidyverse, plotly, rstan, and htmlwidgets), Linux,
Emacs/ESS, Git, CircleCI, GitHub Actions, RStudio, python, docker,
HTML, JIRA, Scrum, SQL </p></li>
<li><p> Past: SAS, C, Java, MS Office, MATLAB </p></li>
</ul>
</section>
<section>
<h1>Certifications</h1>
<ul>
<li><p> SAFe Practice Consultant (SPC) (2024)</p></li>
<li><p> SAFe Practice Consultant (RTE) (2024)</p></li>
<li><p> SAFe Advanced Scrum Master (SASM) (2024)</p></li>
<li><p> Professional Agile Leadership - Evidence Based Management (PAL-EBM) (2024)</p></li>
<li><p> Certified Agile Leader (CAL 1) (2024)</p></li>
<li><p> Professional Scrum Master II, 2024</p></li>
<li><p> Professional Scrum Product Owner I, 2024</p></li>
<li><p> Professional Scrum Facilitation Skills I, 2024</p></li>
<li><p> Introduction to Relational Databases (IBM/Coursera), 2024</p></li>
<li><p> Python Project for Data Engineering (IBM/Coursera), 2024</p></li>
<li><p> Python for Data Science, AI \& Development (IBM/Coursera), 2023</p></li>
<li><p> Professional Scrum Master I, 2022</p></li>
</ul>
</section>
<section>
<h1>Open-Source Software</h1>
<ul>
<li><p><code>RefManageR</code> an R package available on CRAN, for
which I am sole author and maintainer. The package allows for
importing, printing, and working with and bibliographic references in
R.</p></li>
<li><p><code>refund</code> an R package available on CRAN for
regression with functional data. I
have contributed the following components that allow for fitting,
prediction, and visualization of functional generalized additive
models: <code>fgam(), af(), lf(), predict.fgam(),
vis.fgam()</code>.</p></li>
<li><p>Online Appendix to "Functional Generalized Additive Models", containing R code used in simulations.</p></li>
</ul>
</section>
<section>
<h1>Honors, Awards, & Fellowships</h1>
<ul>
<li><p>NSERC PGS-D, 2011-2013</p></li>
<li><p>NSERC PGS-M (CGS-M Declined), 2008-2009</p></li>
<li><p>NSERC Undergraduate Student Research Award, University of Manitoba, 2007 and 2008</p></li>
<li><p>Dr. Cyril H. Goulden Memorial Scholarship, 2008</p></li>
<li><p>U. of M. Students Union Scholarship, University of Manitoba, 2005, 2006, and 2007</p></li>
<li><p>Queen Elizabeth II Entrance Scholarship, 2004-2005</p></li>
</ul>
<p>Publications, talks, and software are available on the other tabs of my webpage.</p>
</section>
<section>
<h1>Academic Experience</h1>
<h2>Cornell University</h2>
<ul>
<li><p>Teaching Assistant, Basic Engineering Probability and Statistics, Summer 2012</p></li>
<li><p>Graduate Research Assistant, David Ruppert, Summer 2011</p></li>
<li><p>Teaching Assistant, Data Mining, Spring 2011</p></li>
<li><p>Teaching Assistant, Basic Engineering Probability and Statistics, Fall 2010</p></li>
<li><p>Graduate Research Assistant, David Ruppert, Summer 2010</p></li>
<li><p>Graduate Research Assistant, David Matteson, Shane Henderson,
and Dawn Woodard, 2009-2010</p></li>
<li><p>Teaching Assistant, Basic Engineering Probability and Statistics, Fall 2009</p></li>
<li><p>Teaching Assistant, Introductory Engineering Stochastic Processes I, Spring 2009</p></li>
<li><p>Teaching Assistant, Basic Engineering Probability and Statistics, Fall 2008</p></li>
</ul>
<h2>University of Manitoba</h2>
<ul>
<li><p>Undergraduate Research Assistant, A. Thavaneswaran, Summer 2008</p></li>
<li><p>Undergraduate Research Assistant, Ruppa K. Thulasiram, Summer 2007</p></li>
</ul>
</section>
<section>
<h1>Professional Activities</h1>
<ul>
<li><p>Referee for Biometrics, Biometrika, Journal of the American
Statistical Association, Environmetrics, Journal of
Computational and Graphical Statistics, Journal of the Royal
Statistical Society: Series C, Computational Statistics and Data
Analysis, Journal of Multivariate Analysis, Statistica Sinica,
Journal of Statistical Software, Statistical Modelling</p></li>
<li><p>Cornell Operations Research Graduate Student Association
President, 2011-2012</p></li>
</ul>
</section>
<section>
<h1>Talks and Poster Presentations</h1>
<ul>
<li><p>Restricted Likelihood Ratio Tests for Regression with Functional Data</p>
<ul>
<li><p>2014 WNAR/IMS Conference, Honolulu, HI, June, 2014 (invited)</p></li>
<li><p>ENAR 2014 Spring Meeting, Baltimore, MD, March, 2014 (contributed)</p></li>
</ul></li>
<li><p>Reproducible Research and Dynamic Documents with R</p>
<ul>
<li><p>IAMCS Machine Learning and Applied Statistics Workshop Series,
College Station, TX, 2014 (invited)</p></li>
</ul></li>
<li><p>Authoring R packages</p>
<ul>
<li><p>IAMCS Machine Learning and Applied Statistics Workshop Series,
College Station, TX, 2014 (invited)</p></li>
</ul></li>
<li><p>Functional Generalized Additive Models</p>
<ul>
<li><p>Department of Statistics, University of Auckland, Auckland,
New Zealand, August, 2017 (invited)</p></li>
<li><p>Annual Conference of the German and Austrian Statistical
Association, Vienna, Austria, September, 2012 (invited)</p></li>
<li><p>ORIE PhD Student Colloquium, September, 2012 (talk)</p></li>
<li><p>Imaging, Communications and Finance: Stochastic Modeling of
Real-world Problems, Columbia University, June, 2011 (poster)</p></li>
<li><p>SAMSI Closing Workshop on the Analysis of Object Data, SAMSI,
Research Triangle Park, June, 2011 (poster)</p></li>
<li><p>Statistical Methods for Very Large Datasets Conference, Johns
Hopkins University, June, 2011 (poster)</p></li>
<li><p>Joint Statistical Meetings, Vancouver, Canada, August, 2010 (talk)</p></li>
</ul></li>
<li><p>SCoOp: Statistical Computation of Option Prices (poster)</p>
<ul>
<li><p>University of Manitoba</p></li>
</ul></li>
</ul>
</section>
</body>
</html>