Well-rounded epidemiologist and computational geneticist with 15 years of experience probing causes of diseases in human populations.

What's the probability that a test result is real given the performance of an assay and the population prevalence of disease? How does one ring a physician and say her newborn patient may have a life-threatening metabolic disorder when the test result could be a false-positive? What happens if the parents of the presumptively ill newborn flew to Hawaii? Do we track them down (send a helicopter across the ocean) or get another test after their vacation? The pressure put on the doctor and parents depends on the prior probabilities. That was my first epidemiological job. It all started with Bayesian reasoning, risk communication, and a deep desire to save lives in real time. This was integrative, applied epidemiology, a position that required a master's in public health (MPH), which I didn't yet have. But the then Director of Newborn Screening (state government) didn't have one either. We both had other master's degrees (mine in applied linguistics). He gave me the same shot he had, and it made me fall in love with epidemiology and genetics. Soon after, I went and got that MPH -- left Seattle for Baltimore (Johns Hopkins University) "to save lives millions at a time" (Hopkins' motto). From there, I studied cancer-predisposition disorders (e.g., ribosomopathies) with epidemiological and biostatistical methods at the National Cancer Institute (Clinical Genetics Branch) and then moved back to beautiful Seattle for my PhD in public health genetics (molecular epidemiology and ethics).

I have subsequently trained at top universities and cancer centers in bioinformatics, machine learning, and post-GWAS methods, such as linkage disequilibrium score regression (heritability and genetic correlation) and Mendelian randomization, a competitive causal-inference technique that mimics a randomized-controlled trial. I have 27 scientific publications, 19 of which are first or senior author, on topics spanning dementia to metabolic disorders, with a special focus on cancer, neurological disorders, and aging. I have been published in top journals, including a soundbite from my dissertation in Nature.

I have two roles at Harvard. I'm a research fellow in the T. H. Chan School of Public Health and a lead investigator for the Scientific Early Life Environmental Health & Development (SEED) Program. For SEED, I am teaching master's students and physicians Mendelian randomization as applied to reproductive health and aging.