Dr. Tao Ye, an assistant professor in the Department of Civil, Environmental, and Ocean Engineering, received a CAREER award from the National Science Foundation (NSF) for his research on using AI to help make public drinking water safer.
According to the NSF, this award is offered “in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.” CAREER award selection is based on two criteria, which are “1) performance of innovative research at the frontiers of science, engineering, and technology that is relevant to the mission of the sponsoring organization or agency; and 2) community service demonstrated through scientific leadership, education, or community outreach.”
Ye’s award, titled “CAREER: Data-Driven Prioritization and Control of Disinfection Byproducts in Drinking Water,” consists of a $550,000 grant. His research focuses on detecting disinfection byproducts (DBPs), which are “created when chlorine and other chemical agents interact with organic material in source water. Some of the most commonly studied byproducts include trihalomethanes such as chloroform and haloacetic acids, which have been linked to increased bladder cancer risk and liver toxicity after long-term exposure. Other compounds, including nitrosamines, are considered potent carcinogens even at very low concentrations, while certain brominated and iodinated byproducts—often associated with coastal or impacted source waters—have shown elevated toxicity in laboratory studies.”
Although some DBPs are regulated by the United States Environmental Protection Agency (EPA), they occur at very low concentrations, making them difficult to detect and study. Researchers have spent decades studying how individual compounds form, but since there are so many possible chemical combinations, comprehensive testing is not feasible. AI is used to restrict the field to contaminants that are most likely to form under real-world conditions, allowing researchers to study those compounds first. As Ye explained, “Machine learning gives us a way to learn from this data, identify patterns, and focus our experimental work where it matters most.”
After narrowing down which compounds to study, Ye and his team can investigate why they form and determine how to prevent or reduce them. Ye’s findings, published in Environmental Science & Technology Letters, can then directly help guide water treatment facilities in reducing unsafe chemical reactions while maintaining disinfection effectiveness. Furthermore, Ye’s research results can be used to shape funding, regulation, and legislation, allowing for “a future in which healthy water is not limited to expensive bottled brands and mineral springs, but instead is free and accessible for all.”
Ye emphasized that drinking water remains his focus, but AI serves as a tool that can help refine and further his research to achieve his goals. As he summarized, “AI lets us see the system more clearly. And when you understand the system better, you can protect people more effectively.”
Unequivocally, Ye’s interdisciplinary research demonstrates how AI’s capabilities can be used to streamline the research process.
