Presenter
Nikoli Dryden

Biography
Nikoli Dryden is a research scientist in the Informatics Group of the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL). Previously, he was an ETH Postdoctoral Fellow at ETH Zurich, working with Professor Torsten Hoefler in the Scalable Parallel Computing Laboratory. He completed his PhD in computer science at the University of Illinois Urbana-Champaign, advised by Professor Marc Snir. During his PhD and postdoc, Nikoli worked heavily with members of CASC and many other collaborators.
Nikoli's research focuses on the intersection of high-performance computing and machine learning. He is particularly interested in scalable training of deep neural networks and applying neural networks to scientific and computational simulation datasets. He also works on parallel algorithms and runtimes, graph analytics, and communication and performance optimization.
Nikoli's research focuses on the intersection of high-performance computing and machine learning. He is particularly interested in scalable training of deep neural networks and applying neural networks to scientific and computational simulation datasets. He also works on parallel algorithms and runtimes, graph analytics, and communication and performance optimization.
Presentations
Chair of Sessions
Paper
Artificial Intelligence/Machine Learning
Distributed Computing
Heterogeneous Computing
Performance Optimization
TP
Committee Roles
HPC for Machine Learning Member