William Michael Landau

Education

Landau, W., Niemi, J., and Nettleton, D., “Fully Bayesian analysis of RNA-seq counts for the detection of gene expression heterosis”. Journal of the American Statistical Association, https://doi.org/10.1080/01621459.2018.1497496.
Landau, W. (2018), “The drake R package: a pipeline toolkit for reproducibility and high-performance computing”. Journal of Open Source Software, 3(21), 550, https://doi.org/10.21105/joss.00550.
Niemi, J., Mittman, E., Landau, W., and Nettleton, D. (2015), “Empirical Bayes Analysis of RNA-seq Data for Detection of Gene Expression Heterosis,” Journal of Agricultural, Biological, and Environmental Statistics, 20, 1-15. Available at link.springer.com.
Landau, W. and Liu, P. (2013), “Dispersion Estimation and Its Effect on Test Performance in RNA-seq Data Analysis: A Simulation-Based Comparison of Methods,” PLOS One, 8. Available at journals.plos.org.
Ratliff, B., Womack. C., Tang, X., Landau, W., Butler, L., and Szpunar, D. (2010), “Modeling the Rovibrationally Excited C2H4OH Radicals from the Photodissociation of 2-Bromoethanol at 193 nm,” Journal of Physical Chemistry, 114, 4934-4945. Available at ncbi.nlm.nih.gov.

Landau, W. (2019) “Reproducible workflows at scale with drake”, rOpenSci Community Call, https://ropensci.org/commcalls/2019-09-24/.
Landau, W. (2019) “Machine learning workflow management with drake”, invited 4-hour workshop, R/Pharma Conference.
Landau, W. (2019) “Reproducible Computation at Scale in R”, Harverd DataFest.
Landau, W. (2018) “The drake R package: reproducible data analysis at scale”, R/Pharma Conference.
Landau, W., and Niemi, J. (2016), “A Fully Bayesian Strategy for High-Dimensional Hierarchical Modeling Using Massively Parallel Computing”. Joint Statistical Meetings, Section on Statistical Computing, Section on Statistical Graphics, Statistical Computing and Graphics Student Awards — Topic Contributed Papers. https://ww2.amstat.org/meetings/jsm/2013/onlineprogram/AbstractDetails.cfm?abstractid=307645.
Landau, W., and Liu, P. (2013), “Dispersion Estimation and Its Effect on Test Performance in RNA-Seq Data Analysis”. Joint Statistical Meetings, Biometrics Section, contributed poster. https://ww2.amstat.org/meetings/jsm/2013/onlineprogram/AbstractDetails.cfm?abstractid=307645.

drake, an R-focused pipeline toolkit for reproducible computation and high-performance computing. Part of rOpenSci.
txtq, a minimalist, serverless, socketless message queue for interprocess communication.
proffer, a pprof-based profiler for R code.
R packages fbseq, fbseqCUDA, and fbseqOpenMP. A toolkit for the fully Bayesian analysis of genomic count data.
downsize, and R package to toggle between the test and production versions of large workflows.

2020 Lilly Innovator Award. Awarded for the development of efficient clinical trial simulation software needed for complex designs and trials of potential COVID-19 treatments.
2019 NumFOCUS New Contributor Recognition. Awarded for inclusive and collaborative work with rOpenSci. https://numfocus.org/blog/2019-numfocus-awards.
2017 Lilly Innovator Award. Awarded for leading a successful team effort to modernize Lilly’s internal process for contributing open source software.
Student Paper Award, American Statistical Association Section on Statistical Computing, Jan 2016. Awarded for an early draft of the preprint at arxiv.org/abs/1606.06659.
Vince Sposito Statistical Computing Award, Iowa State University, Aug 2013.
GlaxoSmithKline Industrial Scholarship, Iowa State University, Sep 2011.
Alumni Scholarship, Iowa State University, Aug 2011.

Reproducible research, statistical computing, hierarchical models, Bayesian methods, Markov chain Monte Carlo, high-dimensional data analysis, genomics data analysis, exploratory analysis, visualization, linear and nonlinear models, data mining, machine learning, predictive modeling, multivariate analysis.
High-performance computing, R, R package development, general-purpose graphics processing unit (GPU) computing, CUDA, shell scripting, LaTeX, HTML, CSS.
Past experience with C/C++, MPI, OpenMP, Python, JavaScript, AWK, Fortran.

October 2016 - Present
Eli Lilly and Company
Developed internal statistical tools and capabilities for the design, simulation, and analysis of clinical trials.
Served as the lead statistician in early-phase autoimmune asset teams.
Supported late-phase clinical trial teams with advanced analytics, including clinical program simulation and tailored therapeutics.
Published open-source software packages drake, txtq, and proffer.

May 2013 - Aug 2016
RNA-sequencing Working Group, Department of Statistics, Iowa State University.
Funded by NIH grant R01GM109458 with Drs. Dan Nettleton and Jarad Niemi.
Developed a new fully Bayesian analysis method for high-dimensional genomic datasets using hierarchical models.
Implemented massively parallelized Markov chain Monte Carlo.
Created the fbseq R package to distribute the analysis method.
Implemented and distributed parallel computing backends for CUDA GPUs (fbseqCUDA) and OpenMP (fbseqOpenMP).
Created the remakeGenerator, parallelRemake, and downsize packages to manage, ameliorate, expedite, and accelerate computationally heavy reproducible workflows that are under heavy development.

Aug - Dec, 2012 and 2013.
Department of Statistics, Iowa State University.
GPU computing seminar series at wlandau.github.io/gpu.
Educated faculty and graduate students on massively parallel computing with general-purpose graphics processing units.
Constructed, curated, and distributed slides, video, and example code at wlandau.github.io/gpu and on YouTube.

Led a successful team effort to modernize Lilly’s internal procedure for contributing open source software.
Served as a volunteer moderator in the 2017 National Science Bowl (high school Indiana Regionals).

Founder and leader, Cloud Computing Working Group, Sep - Dec 2015.
Member, Computation Advisory Committee, Sep 2015 - May 2016.
Volunteer instructor, Office of Precollegiate Programs for Talented and Gifted (OPPTAG), Mar 13, 2014.
Fellow, Preparing Future Faculty, Aug 2013 - May 2014.
Assistant Coach, Boxing Club, Aug 2013 - Dec 2013.

Jarad Niemi, PhD advisor and major professor, niemi@iastate.edu.
Dan Nettleton, lead principal investigator of the RNA-sequencing Working Group (Iowa State Department of Statistics), dnett@iastate.edu.
Peng Liu, MS advisor and major professor, pliu@iastate.edu.
Additional references available on request.