Brian Van Essen is the Informatics Group leader and a Computer Scientist at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory (LLNL). He is actively pursuing research in large-scale deep learning for scientific domains and training deep neural networks using high-performance computing systems. He is the project leader for the Livermore Big Artificial Neural Network (LBANN) open-source deep learning toolkit. Additionally, he co-leads an effort to mapping these scientific, data-intensive, and machine learning applications to Neuromorphic architectures. His research interests also include developing new Operating Systems and Runtimes (OS/R) that exploit persistent memory architectures, including distributed and multi-level non-volatile memory hierarchies, for high-performance, data-intensive computing.
Dr. Van Essen joined LLNL in October of 2010 after earning his Ph.D. in Computer Science and Engineering from the University of Washington in Seattle. He also holds a M.S in Computer Science and Engineering from the University of Washington, a M.S in Electrical and Computer Engineering from Carnegie Mellon University, and a B.S. in Electrical and Computer Engineering from Carnegie Mellon University.
AI/Machine Learning/Deep Learning
Big Data Analytics