Projects

Mediation Analysis in Causal Inference

Extending effects defined through mediation (e.g., direct effects) to stochastic interventions and intermediate confounders.

Causal Effects of Stochastic Interventions

Estimation and inference for causal effects based on stochastic treatment regimes, under two-phase sampling, in mediation settings, and for variable importance analysis.

Distractions

The things that keep me from working.

R Packages

Software packages developed to extend the R programming language.

Variance Moderation for Locally Efficient Estimators

Extending variance moderation for the stabilization of data-adaptive, efficient semiparametric estimators in high-dimensional biology.

Identification of differentially methylated positions and regions using techniques from causal inference and statistical machine learning.

Recent Publications

(see CV for a full list)

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A generalization of moderated statistics to data adaptive semiparametric estimation in high-dimensional biology

The widespread availability of high-dimensional biological sequencing data has made the simultaneous screening of numerous biological …

Causal mediation analysis for stochastic interventions

Mediation analysis in causal inference has traditionally focused on binary treatment regimes and deterministic interventions, as well …

Efficient nonparametric inference on the effects of stochastic interventions under two-phase sampling, with applications to vaccine efficacy trials

The advent and subsequent widespread availability of preventive vaccines has altered the course of public health in the twentieth …

Functional profiling identifies determinants of arsenic trioxide cellular toxicity

Arsenic exposure is a worldwide health concern associated with an increased risk of skin, lung, and bladder cancer but arsenic trioxide …

adaptest is an R package for performing multiple hypothesis testing in problem settings commonly encountered in high-dimensional …

Recent & Upcoming Talks

Generalized Variance Moderation for Locally Efficient Estimation in High-Dimensional Biology

Exploratory analysis of high-dimensional biological data has received much attention since the explosion of high-throughput …

Robust Inference on the Causal Effects of Stochastic Interventions Under Two-Phase Sampling, with Applications in Vaccine Efficacy Trials

Much of the focus of statistical causal inference has been devoted to assessing the effects of static interventions, which specify a …

Fair Inference Through Semiparametric-Efficient Estimation Over Constraint-Specific Paths

We consider nonparametrically estimating a parameter of interest under the constraint that a functional of the parameter is bounded. We …

Data-Adaptive Estimation and Inference for Differential Methylation Analysis

DNA methylation is amongst the best studied of epigenetic mechanisms impacting gene expression. While much attention has been paid to …

Teaching

current courses

• Public Health 242C & Statistics 247C: Longitudinal Data Analysis (Fall 2019), as graduate student instructor with Prof. Alan Hubbard

Carpentries workshops

I am an active member of Software Carpentry and Data Carpentry, through which I engage in curriculum development, maintenance of lesson materials, and workshop delivery.