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Katrina Waters
Chief Scientist
Katrina Waters
Chief Scientist
Biography
More than 1,300 Superfund sites dot the United States. They are places with hazardous waste—landfills, mines, and industrial dumping grounds. Katrina Waters is all too familiar with their toxic legacy.
Among her many roles and areas of expertise, Waters is deputy director of the Oregon State University (OSU) – Pacific Northwest National Laboratory (PNNL) Superfund Research Center. Waters leads the center’s Data Management and Analysis Core, providing expert statistical and data science support and software solutions for data management and interpretation. In 2023, Waters and the center made public the OSU/PNNL Superfund Research Program Analytics Portal to provide access to program data.
“One of the big trends in the Superfund field right now is the concept of having multiple exposures to chemicals from a site,” Waters said. “The fact is that people are not exposed to one chemical at a time—they’re exposed to a mixture of chemicals from a site. There are also issues around the fact that remediation of sites doesn't always make it better. Sometimes remediation transforms the chemicals into a different form where they can actually be more toxic than they were before.”
Waters, a PNNL Laboratory Fellow who holds joint faculty appointments with OSU and the University of Washington, is also a chief scientist in the laboratory’s Earth and Biological Sciences Directorate. Waters leads an internal research program at PNNL called the Predictive Phenomics Initiative, which is focused on developing capabilities to measure and manipulate phenotypes of interest for future applications related to the bioeconomy, human health, and environmental sustainability.
In early 2024, Waters and a team of collaborators shared more than 24,000 raw genomics, proteomics, metabolomics, and lipidomics datasets collected over six years for a National Institute of Allergy and Infectious Diseases project focused on studying host response to viral infections.
Waters’ expertise bridges biochemistry, toxicology, infectious diseases, and data science. These days, she is combining machine learning and artificial intelligence with data to make it conform with data-sharing principles—findable, accessible, interoperable, and reproducible.