A PDF version of my CV may be found here. A BibTex file containing citations to may papers may be found here.
- Ph.D. Statistics, University of Washington, June 2015.
- M.S. Statistics, The Ohio State University, June 2012.
- B.S. Mathematics, The Ohio State University, June 2010.
- B.S. Molecular Genetics, The Ohio State University, June 2010.
- Gerard, D., & Stephens, M. (2017). Unifying and Generalizing Methods for Removing Unwanted Variation Based on Negative Controls. arXiv preprint arXiv:1705.08393. [Link to arXiv]
- Gerard, D., & Hoff, P. (2016). A higher-order LQ decomposition for separable covariance models. Linear Algebra and its Applications, 505, 57-84. [Link to LAA][Link to arXiv]
- Gerard, D., & Hoff, P. (2015). Adaptive higher-order
spectral estimators. arXiv preprint
to arXiv] (Accepted for publication by the Electronic Journal
- Gerard, D., & Hoff, P. (2015). Equivariant minimax dominators of the MLE in the array normal model. Journal of Multivariate Analysis, 137, 32-49. [Link to JMVA] [Link to arXiv]
- Pollack, J. D., Gerard, D., & Pearl, D. K. (2013). Uniquely Localized Intra-Molecular Amino Acid Concentrations at the Glycolytic Enzyme Catalytic/Active Centers of Archaea, Bacteria and Eukaryota are Associated with Their Proposed Temporal Appearances on Earth. Origins of Life and Evolution of Biospheres, 43(2), 161-187. [Link to Springer]
- Gerard, D., Gibbs, H. L., & Kubatko, L. (2011). Estimating hybridization in the presence of coalescence using phylogenetic intraspecific sampling. BMC evolutionary biology, 11(1), 291. [Link to BMC]
- Gerard, D., & Stephens, M. Empirical Bayes Shrinkage
Estimation, and False Discovery Rate Estimation, Allowing For
- Abstract: In this paper we combine two important ideas
in the analysis of large-scale genomics experiments
(e.g. experiments that aim to identify genes that are
differentially expressed between two conditions). The first idea
is use of Empirical Bayes (EB) methods to handle the large number
of potentially-sparse effects, and estimate false discovery rates
and related quantities. The second is use of factor analysis
methods to deal with sources of unwanted variation such as batch
effects and unmeasured confounders. By combining the key ideas
from both these lines of research we provide new and powerful EB
methods for analyzing genomics experiments that can account for
both large numbers of potentially-sparse effects and for sources
of unwanted variation that can otherwise confound inference. In
realistic simulations, these new methods provide significant gains
in power and calibration over competing methods. In real data
analysis we highlight that different methods, while often
conceptually similar, can vary widely in their assessments of
statistical significance, highlighting the need for care in both
choice of methods and interpretation of results.
- Stephens, M. (2016). False discovery rates: a new deal. Biostatistics.
- Gerard, D., Ferrão, L. F. V., & Stephens, M. Harnessing
Empirical Bayes and Mendelian Segregation for Genotyping
Autopolyploids with Messy Sequencing Data.
- Abstract: Genotyping by next-generation sequencing
(NGS) is a powerful and popular way to detect single nucleotide
polymorphisms (SNP's) and classify the alleles of
individuals. Genotyping diploid individuals using NGS is a
well-studied field and similar methods for polyploid individuals
are just emerging. However, there are many aspects of NGS data
that remain unexplored by most methods. We provide two main
contributions in this paper: (1) many datasets feature related
individuals, and so we use the structure of Mendelian
segregation to build an empirical Bayes approach for genotyping
polyploid individuals; (2) we additionally draw attention to and
then model common aspects of NGS data: sequencing error,
read-mapping bias, overdispersion, and outlying observations. We
verify our method in simulations and apply it to a dataset of
hexaploid sweet potatoes (Ipomoea batatas).
- Postdoctoral Scholar under Professor Matthew Stephens: 09/2015 - Present
- Developing empirical Bayes methods to account for hidden
confounding in large scale gene expression studies.
- Efficiently implementing these methods in R and C++.
- Rigorously testing these methods using Monte Carlo methods.
- Leading/mentoring graduate students on their individual projects.
- Authoring reports and academic papers.
- Research Assistant Under Professor
Peter Hoff: 09/2013 - 06/2015
- Studied optimal estimation of covariance matrices in Gaussian
arrays using the notions of equivariance.
- Developed novel tensor decompositions, creating higher-order
versions of well-known matrix decompositions.
- Developed singular value shrinkage mean estimators for
- Research Assistant Under Professor
Verducci: 09/2011 - 06/2012
- Studied monotone association between gene expression and drug
resistance within unspecified subtypes of cancer.
- Undergraduate Research Fellow Under Professors
Laura Kubatko and
Gibbs: 04/2009 - 06/2010
- Studied the hybridization of two subspecies of Missouri
Rattlesnakes and two populations of Black Ratsnakes.
- Duties included sequencing work in the lab, computer programming
using Perl, and data analysis with various programs.
- Lecturer of introductory statistics 06/2013 - 09/2013
- Developed my own lesson plans and slides from which I lectured three times a week.
- Created material for two teaching assistants during their
- Course content included comparisons of good sampling designs
versus bad sampling designs, conditions under which claims of
causality may be made, confounding variables, good and bad measures
for answering questions of interest, describing relationships
between variables, and good and bad graphics to describe data.
- Graduate Teaching Assistant 09/2012 - 06/2013
- Led four one-hour recitation sections of introductory
statistics every week.
- These were small group discussions that acted primarily as
support for the main content taught during lecture.
- Lecturer of introductory statistics 09/2011 - 12/2011
- Lectured to large groups of students using a pre-defined course plan.
- Created my own slides to follow along the lesson plans.
- Phylogenetic Workshop Assistant 06/2011 - 08/2011
- Led a group of undergraduate researchers studying HIV. We
studied the association between evolutionary distance (measured by
branch distance along estimated trees) and clinical variables
collected by an HIV treatment center in Belgium.
- Phylogenetic Workshop Assistant 06/2010 - 08/2010
- Led lab sessions on Unix and various phylogenetic program
- Led a group of undergraduates researching the evolutionary
origins of flightless birds.
- Individually mentored an undergraduate student on phylogenetic
research and statistical analysis with R. We tried to incorporate
protein structure into our gene tree estimates while studying the
evolutionary relationships of HPV.
- Undergraduate Teaching Assistant: 09/2008 - 12/2008
- Taught four one-hour recitation sections of intermediate
algebra every week.
- Z.W. Birnbaum Award for the best general exam of the 2013-2014 academic year.
- Distinguished University Fellowship (September 2010 - June 2012).
- Graduated Summa Cum Laude (June 2010).
- Award for excellent research presentation at the BMPS Poster Forum (23 April 2010).
- Medalist Scholarship (September 2006 - June 2010):
- For academic excellence and essay writing skills.
- President's Salute Nominee (April 2010):
- For academic excellence among peers from the college of Arts and Sciences.
- R Packages: tensr,
- Advanced training: R, \LaTeX.
- Intermediate training: C++, Shell.
- Familiar: Python, Matlab/Octave, Mathematica.