Rachael Phillips

Bio/CV: 

Rachael V. Phillips is a PhD student in Biostatistics at the University of California at Berkeley, mentored by Prof. Mark van der Laan. Her current work includes clinical applications of the personalized online super learner, automated targeted learning (TL) development, and a TL demonstration project for the US Food and Drug Administration with Dr. Susan Gruber. She is an author of tlverse software, including super learner (sl3), and highly adaptive lasso (hal9001), and cross-validation (origami) packages. Rachael was integral in the development of a recently-approved course series on TL: Targeted Learning (Public Health 243A) and Targeted Learning in Practice (Public Health 243B); she previously directed the transition to blended learning for existing TL-related courses.

Research interests: 

targeted learning, super/machine learning, online learning, causal inference, human-computer interaction, intelligence augmentation, personalized optimization, statistical process control

Publications

Jeremy Coyle; Nima Hejazi; Ivana Malenica; Rachael Phillips; Alan Hubbard; Mark van der Laan
Book,