Background
My PhD research sat at the intersection of math and computational biology: developing new mathematical frameworks to find patterns across large, messy genomic datasets, and using them to build a genomic-based prognostic indicator for ovarian cancer. That's where I learned to be rigorous about separating real signal from noise — a habit that's shaped how I approach every dataset since, well outside of biology. The full technical write-up is here for anyone who wants the details.
Interests
I'm interested in problems where the gap in our knowledge is closed less by more data and more by better logic and methodology borrowed from other fields. My focus has stayed on pushing what's possible to discover from data and applying it to problems that matter. If you've got an interesting, hard problem in that space, let's talk.
Hobbies
Outside of work: climbing, biking, hiking, skiing, running, remote control cars and helicopters, and board games.
Publications
P. Sankaranarayanan,* T. E. Schomay,* K. A. Aiello, and O. Alter, "Tensor GSVD of Patient- and Platform-Matched Tumor and Normal DNA Copy-Number Profiles Uncovers Chromosome Arm-Wide Patterns of Tumor-Exclusive Platform-Consistent Alterations Encoding for Cell Transformation and Predicting Ovarian Cancer Survival," Public Library of Science (PLoS) One 10 (4), article e0121396 (April 2015); doi: 10.1371/journal.pone.0121396.
L. A. Portelli, T. E. Schomay, and F. S. Barnes, "Inhomogeneous Background Magnetic Field in Biological Incubators is a Potential Confounder for Experimental Variability and Reproducibility. Bioelectromagnetics 34 (5), 337-348. (July 2013)