I am a fourth-year PhD Candidate in Statistics at Harvard University; my advisors are Tirthankar Dasgupta, Luke Miratrix, and Donald RubinMy main research interests are in experimental design and causal inference. In 2016 I was lucky enough to receive a three-year NSF Graduate Research Fellowship to make the statistical design of experiments and observational studies more flexible for practitioners, especially when they want estimation to focus on particular background information or effects. For more details on my current research, please see my research page.

Before Harvard, I received a B.S. in Economics and Statistics and a B.A. in Professional Writing from Carnegie Mellon University in 2014. Originally, I majored in Mathematics, but my math professors kept getting upset that I was asking so many applied questions. I found that Statistics professors - like my academic advisor Rebecca Nugent - welcomingly connected theory to the real world.

While at Carnegie Mellon, I participated in several applied projects with Pittsburgh Public Schools to determine what affects attendance and dropout rates. This is my token "when I fell in love with statistics" story, because I discovered the impact that proper statistical methods - both ones you can find in textbooks and ones you have to create - can have on individuals and communities. This work later inspired my senior honors thesis on propensity score methodologies (advised by Howard Seltman).

Before Cambridge and Pittsburgh, I was born and raised in Louisville, Kentucky, where I received an excellent education from Jefferson County Public Schools. In my spare time I run along the Esplanade; read non-statistics books; play squash, guitar, and chess; and write album and concert reviews for the music webzine ScenePointBlank.