Dr. Andrew J. Holbrook is an Assistant Professor of Biostatistics at University of California, Los Angeles (UCLA). He received his Ph.D. working with Professor Babak Shahbaba at University of California, Irvine, studying statistical methods for neural decoding and the analysis of longitudinal magnetic resonance imaging (MRI). He completed his postdoctoral training at the UCLA Department of Human Genetics, where he worked with Professor Marc Suchard to develop high-performance computing (HPC) tools for viral phylogeography. Dr. Holbrook’s research focuses on HPC strategies for big data statistical inference and the incorporation of deep learning into highly-structured statistical models. He is a recipient of both an NSF CAREER Award and an NIH K25 Award for quantitative research in biomedicine. For Dr. Holbrook, the “Data Science Laboratory” is a hub for interdisciplinary research and cross-pollination and is, therefore, central to 21^st century science.

To learn more about Dr. Holbrook’s research, please visit his professional website.