36 in peer-reviewed scientific journals
12 internal technical reports
24 at scientific meetings
10 technical presentations
on 100+ scientific projects as a non-author
using R, Python, C, SQL, SAS, C#, Visual BASIC
in statistics & data mining for internal/external workgroups and mid-level leadership
for 6 scientific journals
Awarded the Jerome L. Clutter Memorial FELLOWSHIP for outstanding student research
Inducted into the Xi Sigma Pi International Forestry HONOR SOCIETY
Dissertation: Sampling efficiencies of new and existing variable radius plot growth estimators
Coursework including Probability Theory I & II, Mathematical Statistics I & II, Non-linear Regression, Time Series Analysis, Numerical Computing
Thesis: Using a camera as an angle gauge in angle-count sampling
With an emphasis on quantitative decision making
I used Bayesian Model Averaging in R for model selection, to assess variable importance, predict new cases, and assess model uncertainty in multiple scientific projects.
I used Python and R to create a web application that aids researchers in the deign of multi-stage, stratified cluster surveys. It computes the needed sample size -- or tells the researcher what size confidence interval can be achieved for a given sample size -- and outputs tables, graphs, and summary statements suitable for use in protocols and manuscripts.
I invented algorithms to quickly compute the Type I error rate of sequential A/B tests under both a Binomial & Poisson design. I coded the algorithms in C, with optional interfaces in R or as a stand-alone DLL. My code also computes exact-test critical value, statistical power, & lists decision-making data points. Runtime < 1 second -- 3 seconds; the code it replaced required overnight-to-days.
A framework using Python to convert a collection of Markdown files into a website.
Winner of CDC's Best Theoretical Paper award
Time-varying boundaries to controll type I error over the course of sequential A/B testing
Winner of CDC's Best Theoretical Paper award
The frequentist FPR was better, but the Bayesian time-to-signal & FNR was lower
Highlighted the unified manner in which estimation and prediction are handled
The bias-variance tradeoff is better handled in predictive modeling with guarded parameter-space flexibility
The best of both worlds. Sometimes it makes sense to write your own C modules. In this talk I shared with colleagues how we can use our C code in R scripts.
Bayesian statistics represent a powerful paradigm for all forms of statistical inference. I gave this introductory-level talk to fellow scientists.
The days before Jupyter Notebooks. This is a talk I shared with colleagues on existing methods to do reproducible research.
Two-time winner of BEST THEORETICAL PAPER, CDC’s Statistical Science Award for Statistical Excellence:
Continuous Sequential Boundaries for Vaccine Safety Surveillance Stat in Med (33):19
A Bayesian Approach to Sequential Analysis in Post-licensure Vaccine Safety Surveillance Pharm Stat (19):3
HONOR AWARD, National Center for Emerging and Zoonotic Infectious Diseases (NCEZID), for:
Excellence in rapidly assessing the safety of Tdap vaccination in pregnant women.
CERTIFICATE OF APPRECIATION, CDC Division of Tuberculosis Elimination, for:
Exemplary collaboration & innovation in quantitative science to respond to the leveling of Tuberculosis incidence.
DIRECTOR’S SPECIAL ACT IN RECOGNITION, NCEZID/Division of Healthcare Quality Promotion, for:
Development of innovative methods to aid Rapid Cycle Analysis vaccine safety surveillance activities.
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