Shannon McCurdy is a postdoctoral scholar in computational biology with Lior Pachter at the California Institute for Quantitative Sciences at UC Berkeley. She is a recent transplant into the field of computational biology; her dissertation was on theoretical physics. Her broad interest is in the underlying mathematical models for biological problems. More specifically, she is interested in applications of statistical modeling, machine learning, and graph theory to biological contexts. Her current research is on the assembly of a highly repetitive DNA sequences from next-generation sequencing data and on the effects of population structure on associations between genetic variation and gene expression.