Christopher J. Earls

Christopher J. Earls is the J. Preston Levis Professor of Engineering at Cornell University, affiliated with the Department of CE. His research focuses on developing novel mathematical and computational approaches to gain deep understanding of natural and engineered systems. His work addresses practical challenges related to the principled treatment of uncertainty, sparse sensing, and intrinsic complexity. The intellectual themes underlying his research include applied mathematics and artificial intelligence.

Christopher Earls J. Preston Levis is a Professor of Engineering at Cornell University, specializing in Applied Mathematics, AI, Mechanistic Interpretability, and Interpretability. His research focuses on leveraging deep learning to discover partial differential equations from limited and noisy data, as well as developing human-readable models for complex systems. He explores the application of AI in structural engineering, including structural health monitoring, material behavior under stress, and the use of fiber-reinforced polymer composites to enhance ductility. His work also addresses the mechanical properties of high-performance steels and the influence of geometric factors on structural behavior. His research bridges computational methods with real-world engineering challenges, emphasizing interpretability and data-driven discovery.