About

Lu Wang is a highly skilled computational mathematician with over 8 years of experience in fast linear solvers for large-scale problems. She has worked extensively on algebraic multigrid methods (AMG) on exascale parallel machines for solving linear systems from reservoir simulations. She is also experienced in GPU implementations for hypre package. Lu is currently working as a Senior Software Engineer at Databricks, where she is leading the ML training team. Her responsibilities include developing and maintaining machine learning tools and platforms on Databricks, such as Databricks runtime for ML, AutoML, and sparkdl. Prior to her current role, Lu has worked as a Software Engineer at Databricks and as a Postdoctoral Researcher at Lawrence Livermore National Laboratory. During her time at Lawrence Livermore, she performed research in the theory and development of algebraic multigrid solvers for the solution of linear systems that arise from reservoir simulations in the oil and gas industry. She also developed partial assembly algorithms for MFEM and implemented GPU versions of hypre software. Lu holds a Doctor of Philosophy (PhD) in Computational Mathematics from Penn State University and a Bachelor's degree in Computational Mathematics from Peking University. She is interested in any area with interesting mathematical/computational problems to solve, especially those involving linear solvers. Her technical skills include software engineering, machine learning, Databricks, and research science. Lu is a highly motivated and talented individual who is always eager to learn and expand her skill set.