Rollin Thomas is a Big Data Architect in the Data and Analytics Services group at the National Energy Research Scientific Computing Center (NERSC), located at Lawrence Berkeley National Laboratory (LBNL). There he leads efforts to support Python users on the Cray XC30 Edison and Cray XC40 Cori systems. He also coordinates the NERSC Exascale Science Application Program for Data, an effort to prepare data-intensive science codes (many written in Python) for near-term and future many-core architectures.
Rollin received his PhD in Physics with Astrophysics Concentration from the University of Oklahoma in 2003, where he focused on the application of Monte Carlo methods to radiative transfer simulations of multidimensional supernova atmospheres. After his PhD he worked on several supernova cosmology experiments at LBNL, where he contributed thousands of lines of Python code for scientific data management, automated data acquisition, and pipelined data reduction and analysis. He joined NERSC in 2015.