Beef cattle have experienced massive gains in virtually every measure of efficiency over the last 50 years. Much of this progress can be attributed to improvements to the genetics of these populations. Tools for performing more accurate selection (EPDs, genomically-enhanced EPDs) have further accelerated genetic progress. Despite this improvement, further increases in efficiency will be critical for meeting the global demand for protein while continuing to reduce the beef industry's environmental footprint. This effort all starts with identifying and selecting efficient cows. Cow efficiency is a multi-faceted problem that entails fertility, health, feed efficiency, and environmental adaptation. My research program aims to use genomics and high-throughput phenotyping to identify and select more efficient cows. This work relies on accurate phenotypes from large cohorts of animals. As a result, I am interested in using high-dimensional information collected through imaging or sensors to develop phenotypes for hard-to-measure traits like health status, feed efficiency, or structural soundness. My research program is also interested in identifying the genetic variants that underlie these phenotypes and others using genome-wide association studies (GWAS). Beyond mapping trait-associated variants, we are interested in layering multiple forms of "omic" data (genomic, transcriptomic, metabolomic) to identify important functional variants and determine how they modulate complex biology. Finally, we want to understand environmental adaptation and/or robustness in cattle populations. As the climate becomes more volatile, producing animals that are genetically able to cope with environmental stressors will be essential. I am passionate about working together with academics, students, producers, and allied industry to explore these questions and deliver truly translational research to the beef industry.