Data-Driven Environmental Chemistry
We work at the interface of environmental chemistry, nanotechnology, and machine learning:Â
We work at the interface of environmental chemistry, nanotechnology, and machine learning:Â
We aim to develop data-driven approaches to understand the complex interactions that exist in environmental chemistry, and leverage these interactions for beneficial applications, including but not limited to environmental monitoring and remediation, materials development, process optimization, and in silico toxicity.