Los Alamos National LaboratoryInformation Science and Technology Institute (ISTI)
Implementing and fostering collaborative research, workforce and program development, and technical exchange

Project Descriptions

Using big data technologies to gain insights from scientific data.



  • Program Co-Lead
  • David Rogers
  • Program Co-Lead
  • Terry Turton
  • Program Co-Lead
  • Ollie Lo
  • Program Co-Lead
  • Jesus Pulido

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Project Focus Areas for 2023:

 Focus Area 1: In Situ Data Analysis and Visualization Workflows

As high performance computing moves into exascale range, the post hoc analysis paradigm will shift to in situ.  In situ data analysis and visualization selects, analyzes, reduces, and generates extracts from scientific simulation results while the simulation is running to overcome bandwidth and storage bottlenecks.  The results are scientific workflows that combine in situ and post hoc analysis into a full pipeline.

Projects in this focus area will give students the opportunity to build sophisticated pipelines to run simulation codes on HPC resources; develop in situ analysis and visualization algorithms; and apply compression techniques to real world data.  Complementary projects will focus on post hoc reconstruction, analysis techniques, and validation of the in situ workflows. 

 Focus Area 2: Machine Learning for Data Science and Visualization

Machine learning techniques have become an important analytical tool for data science in recent years.  Projects in this focus area will give students hands-on experience in applying ML/AI techniques to various novel data analysis and visualization problems such as in situ feature exploration in scientific simulations, image analysis, uncertainty quantification, data reduction, and integrating ML/AI techniques into analysis workflows. 

 Focus Area 3:Data Science Infrastructure

Helping scientists manage their data and analysis workflows supports the development of scientific insight.  Projects in this focus area will on developing data science infrastructure and user interfaces that support specific scientific workflows and data analytics. 

 Focus Area 4: Other Areas of Expertise

Data Science at Scale mentors have expertise in areas such as vector topology, scientific visualization applications, human perception in visualization, color theory, interactive visualization techniques, uncertainty quantification. Funding for research projects in these areas may become available and we welcome applications focused on these areas.