From data modeling to task simplification, the Department of Civil and Environmental Engineering embraces artificial intelligence as a powerful tool to complement our world-class research and teaching.
Professor Mazdak Arabi and the One Water Solutions Institute partner with federal, state, and industry to develop and apply AI for field-based and remotely sensed data and next generation modeling tools for sustainable management of water and natural resources, sustainable agricultural systems, and resilient infrastructure systems.
Associate Professor Ryan Bailey and M.S. student Kenneth Laffite use machine learning to create models for how salt moves through water systems, impacting crop production in Colorado.
Teaching Associate Professor Dan Baker promotes using AI to brainstorm and complete mundane tasks, allowing students and educators more time for innovation.
Associate Professor Ellison Carter and Ph.D. candidate Collin Brehmer study air quality in Beijing and use machine learning to estimate the impact of replacing coal heating with clean energy.
Assistant Professor Frances Davenport and Ph.D. student Michael Talbot leverage AI to build models for thousands of watersheds to increase their understanding of how hydrologic systems respond to climate change, particularly with flooding and extreme runoff events.
Associate Professor Yanlin Guo uses machine learning to develop prediction models for the wind load of high-rise buildings with glass exteriors when variables change, such as the addition or removal of surrounding buildings and changes in wind intensity or speed.
Associate Professor Ryan Morrison uses machine learning to detect artificial levees in the national database, which can cause complex changes in river-floodplain connectivity and can increase flooded areas around rivers.
Professor Sybil Sharvelle is developing circular fit-for-purpose water treatment and sensing technology using AI and the Water Technology Acceleration Platform.
