About me

I’m currently a PhD student in the Program in Population Health Sciences and the Department of Epidemiology at the Harvard T.H. Chan School of Public Health. I’m also completing a Master of Science degree in the Department of Epidemiology. My research interests are in epidemiologic and biostatistical methods as well as reproductive and child health. I developed these interests at U.C. Berkeley, where I earned my M.S. in epidemiology, and while teaching third grade at Little Wound School in Kyle, SD, where I lived for three years. Prior to that I studied comparative literature (focusing on literary translation from French and Portuguese) and community health at Brown University.

My passion for teaching has continued beyond my experience in elementary education. I enjoy introducing students to epidemiology and biostatistics as well as delving into more advanced topics in causal inference. I love to create teaching materials, some of which can be found below.

I also love hiking and camping, reading novels, and programming in R.


Understanding the way in which a study sample relates to the target population is critical for avoiding and addressing bias. …

We extend a sensitivity analysis approach for selection bias to account for poor control selection in case-control studies.

Online tools and projects

Introduction to R

An short course to teach R basics to epidemiology students.

Simple sensitivity analysis for selection bias

An online tool to help assess the possible extent of selection bias.

PHS 2000 summer preparation

A learnr tutorial to introduce first-year PhD students in Population Health Sciences to probability, statistics, and R.

R office hours

A collaborative effort to develop weekly teaching materials for R help.


Courses for which I’ve been a instructor/teaching fellow

Introduction to R

Developed and taught short course to introduce R to graduate students. Topics included creating figures and tables, cleaning data, writing functions.

Advanced Epidemiologic Methods

Causal inference for time-varying exposures: g-formula, marginal structural models, g-estimation of structural nested models; static and dynamic treatment regimes

Quantitative Research Methods in Population Health Sciences

Regression models, sampling, longitudinal and multilevel analysis, time-varying confounding, mediation and interaction, econometric methods, missing data

Introduction to Epidemiology and Human Disease

Basic epidemiologic methods, overview of epidemiology of diseases/conditions of public health importance

Epidemiologic Methods

Study design, sampling, data collection, analysis, inference


You can contact me here or send me an email.