Twitter: @LoftusPhD

I am a statistician interested in data science, high-dimensional statistics, and Gaussian processes. More broadly, I am interested in statistical theory and methodology driven by applications in biostatistics or motivated by social good.

Much of my research is with Jonathan Taylor in a new area called selective inference. This work involves challenging mathematical and computational aspects of conducting inference for selection procedures with complicated underlying geometry. For example, my research enables significance testing after use of some of the most popular model selection procedures such as the Lasso with regularization chosen by cross-validation, or forward stepwise with number of steps chosen by AIC or BIC.

I am co-author, along with Rob Tibshirani and others, of the selectiveInference R package implementing these methods.

As a first generation college graduate, my higher education journey began in community college and I have great appreciation for all the teachers and assistance I have received along the way. I am an active member of student groups advocating diversity and participate in a mentorship program for first-generation undergrads.

Ph.D. Statistics, (Biostatistics trainee), Stanford University, expected 2016.
M.A. Mathematics, (concentration in computational biology), Rutgers University, 2011.
B.S. Mathematics, (summa cum laude), Western Michigan University, 2009.

Departmental Teaching Award, 2014.

Alan M. Abrams Memorial Fellowship, 2013-2015.

GAANN Fellowship, Rutgers University, 2009-2012.

Phi Beta Kappa