Talks & workshops

Events I have been invited to present at, shared along with slides, videos, and other linkable resources.


Sensitivity Analysis for Unobserved Effect Modification when Generalizing Findings from Randomized Trials to Target Populations

Event description: This half-day workshop will inform efforts by the interagency Federal Committee on Statistical Methodology (FCSM) to improve information shared with the public about how agencies combine data from multiple sources to produce estimates, analyses and other data products. The workshop will provide insight into a critical aspect of integration processes, namely, identifying and evaluating critical assumptions made during integration, and the possible impact on results when those assumptions are changed.

June 10, 2019

3:30 PM – 4:00 PM

FCSM/WSS Workshop on Sensitivity Analysis with Integrated Data / Washington, DC

Using Statistics and Data Science for Public Health and Social Good

Traditionally, many public health studies have started off as research questions, answered by identifying and analyzing an appropriate dataset. However, in some cases, the existence of data precedes (and therefore drives) the scientific question, and with the emergence of big data and the growth of data science as a field, this is becoming increasingly common. I will be giving an overview of three different types of data I have encountered in projects as a biostatistician, where aspects of each data source have inspired each of the respective projects.

April 2 – 3, 2019

4:00 PM – 5:30 PM

George Mason University, National Public Health Week / Johnson Center, 327, Meeting Room C, Fairfax Campus

Calibrating Validation Samples when Correcting for Measurement Error in Intervention Study Outcomes

Many lifestyle intervention trials depend on collecting self-reported outcomes, such as dietary intake, to assess the intervention’s effectiveness. Self-reported measures are subject to measurement error, which may impact treatment effect estimation. Methods exist to correct for measurement error using external validation studies, which measure both the self-reported outcome and accompanying biomarker, to model the measurement error structure. However, there is growing concern over the performance of these methods when the validation study differs greatly from the intervention study on pre-treatment covariates that relate to treatment effect.

March 26, 2019

8:45 AM – 9:00 AM

ENAR Spring 2019 Meeting / Philadelphia, Pennsylvania

Building a Personal Website using R

There are many great reasons to create a personal academic website as a graduate student. I will be walking students through this very helpful tutorial by Alison Hill on building a personal website using R Studio and Blogdown, and try to show students how easily they can create and update a website to highlight their research achievements and upcoming talks, and begin to form their online academic identity!

February 26, 2019

12:15 PM – 1:15 PM

JHU Biostatistics Student Computing Club / Baltimore, Maryland


Reproducible Data Science: Building a Code Pipeline from End to End

Using my experience as a 2018 Data Science for Social Good Fellow, I will be providing an overview of our team’s workflow and pipeline construction, highlighting the importance of reproducibility and easy implementation of our code. The talk is divided into the different sections of our pipeline: 1) Data processing and cleaning, 2) Data staging, 3) Machine learning modeling infrastructure, and 4) Usability. Each stage is discussed in context of our DSSG project, in which we constructed a precision medicine tool to predict an individual’s risk of developing Type 2 Diabetes within the next 3 years.

September 18, 2018

12:15 PM – 1:15 PM

JHU Biostatistics Student Computing Club / Baltimore, Maryland