Brian Van Esser is a computer scientist at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory. He is actively pursuing research in training deep neural networks on high-performance computing systems. His research interests also include developing new operating systems and runtimes that exploit persistent memory architectures, including distributed and multi-level non-volatile memory hierarchies, for high-performance, data-intensive computing. Additionally, he is interested in opportunities related to mapping these scientific, data-intensive, and machine learning applications to neuromorphic architectures. Brian joined LLNL in 2010 after earning his Ph.D. in computer science and engineering from the University of Washington in Seattle.