Mentors

Ayan joined the Data Science at Scale team as a postdoctoral researcher in January 2017, transitioning to a staff scientist in April 2018. He received his Ph.D. in Computer Graphics and Visualization from The Ohio State University in December 2016 and is a graduate of the DSS Summer School (2013-2016).   His current research focuses on in situ data reduction and modeling for extreme-scale data. His projects include Machine Learning for data exploration, visualization, and uncertainty quantification. He has also worked with flow field data and particle tracing using streamlines and stream surfaces and on time-varying multivariate data exploration and using information theory to provide insights into data.

Chris received his Ph.D. in Physics from Syracuse University in 2017. He began his research in gravitational-wave astronomy focusing on the detection and parameter estimation of binary black hole and neutron star mergers. Since 2018, Chris has been a staff scientist in the Data Science at Scale team. His experience at Los Alamos and research interests include data analysis of physical experiments, optimization of analysis methods, and developing scientific workflows.

Vita

Dr. Roxana Bujack is a staff scientist in the Data Science at Scale Team at Los Alamos National Laboratory since July 2016. She graduated in mathematics and computer science and received her PhD in the Image and Signal Processing Group at Leipzig University. Then, Roxana worked as a postdoctoral researcher at IDAV at the University of California, Davis and at the Computer Graphics and HCI Group at the Technical University Kaiserslautern. Her research interests include visualization, pattern recognition, vector fields, moment invariants, high performance computing, massive data analysis, Lagrangian flow representations, and Clifford analysis.

Soumya is a scientist in the Data Science at Scale (DSS) team of CCS-7 at Los Alamos National Laboratory since July 2019. He worked as a postdoc in the DSS team from June, 2018 to July, 2019. Soumya got his Ph.D. in Computer Graphics and Visualization from the Ohio State University in May 2018. Prior to joining as a postdoc, Soumya was a summer student at LANL from 2015 to 2017. His areas of interest includes in situ extreme-scale data analysis and visualization, statistical data summarization and feature analysis, uncertainty quantification and visualization, and high performance computing.

Website

Pascal joined the Data Science at Scale team as a postdoc, transitioning to Staff Scientist.  He received his Ph.D. in Computing from the University of Utah working on visualization on High-Performance Computing (HPC) Systems. His research interest is in large-scale data visualization and analysis.

Li-Ta Lo a.k.a Ollie received a B.S. in Physics from National Chung-Hsing University in 1995 and a M.S. in Applied Mechanics from National Taiwan University in 1997. He joined Los Alamos National Laboratory in 2003, after working in the semiconductor industry for 4 years. As a multi-disciplined, multi-cultured person, he has enjoyed working with several teams and a diverse set of projects during his career at LANL. His current research interest includes data science, large-scale visualization and analysis, data-parallel programming and software engineering for scientific computing.

John received a B.A. in Anthropology in 1995 and a M.S. in Computer Science in 2011, both from the University of New Mexico. His experience includes data science at scale, large-scale visualization and analysis, data-parallelism, in-situ visualization and analysis.

Jesus Pulido is a staff research scientist for the Data Science at Scale Team since February 2020. He received his Ph.D. in Computer Science at the University of California, Davis under Prof. Bernd Hamann in 2019. He specializes in data analysis, data reduction, visualization, high performance computing, wavelets and multi-resolution methods. He has experience in applications of image sensors, astronomy, turbulence and cosmology.

David Honegger Rogers joined LANL in 2013, after a decade of leading the Scalable Analysis and Visualization Team at Sandia National Labs, where he was instrumental in bringing in-situ analysis and visualization into production. He now focuses on interactive web-based analysis tools that integrate design, scalable analytics and principles of cognitive science to promote scientific discovery. Prior to working on large scale data analysis, David worked at DreamWorks Feature animation, writing and managing production software. He has degrees in Computer Science, Architecture (buildings, not computers), and an MFA in Writing for Children.

Terry Turton is a Staff Scientist in the Data Science at Scale team.  She received her Ph.D. in Physics from the University of Michigan and did postdoctoral work at the Superconducting Super Collider, Michigan State University and the University of Cincinnati. Her current work focuses on data analysis and visualization for exascale science codes.  She works on the Cinema Project (www.cinemascience.org) and ALPINE (alpine.dsscale.org).  She also works on scientific workflow and user evaluation of scientific visualization.