
Computational
Mathematics
& Statistics
Computational
Mathematics
& Statistics
Solving problems with
statistics and mathematics
Solving problems with
statistics and mathematics
Pacific Northwest National Laboratory researchers use nuclear magnetic resonance spectrometers—basically superconducting magnets—to discern between the different chemical structures in fuels. Each chemical interacts with the magnetic field in a different way. Statistician and modeler Alejandro Heredia-Langner links this data to the influence that the chemical structure has on important fuel properties.
Andrea Starr | Pacific Northwest National Laboratory
From subsurface transport to ice-sheet modeling, computational mathematicians at Pacific Northwest National Laboratory (PNNL) develop and enable innovative modeling and simulation methodologies that improve the understanding of complex systems.
As leaders in mathematics research, mathematicians at PNNL develop novel computational modeling and data-analysis tools used to predict and control complex systems and extract hidden features, anomalies, and signatures that support discovery and optimize data-gathering approaches through sampling and experimental design.
Our applied mathematics and statistics capabilities complement research conducted throughout the Laboratory, fueling the fundamental understanding of physical, chemical, and biological principles using computational modeling, experimentation, and data evaluation.
Our work applies fundamental mathematical principles to problems in chemistry, cybersecurity, high-performance computing, and more. We also specialize in applying machine learning and statistics methods to accelerate scientific computations for complex systems, including multiscale, multiphysics, and machine learning algorithm development and implementation.
PNNL is advancing mathematical theory to build strategically intelligent and resilient computational systems. We develop reasoning within artificial intelligence systems to monitor application environments and adapt algorithms to optimally intersect with a dynamic system state.
We design, implement, and validate software, tools, and statistical package products that allow deployable solutions within any research capability. From modeling uncertainty in the power grid and guiding the design of energy systems with simulations—all the way to multiscale modeling for bioremediation to operations research and industrial engineering—our applied mathematics and statistics fuel fundamental understanding of scientific phenomena. PNNL consistently delivers high-quality methods and applications to address critical scientific challenges in national security and energy resilience.