Explores the impact of morphodynamics on the relationship between different scales, particularly within computational plant science.
Research Experience
Focuses on artificial intelligence via high-level symbolic representations (such as computer algebra) and mathematical machine learning. A significant application involves trainable changes of spatiotemporal scale in scientific models, which are very useful for pursuing multiscale science.
Background
Professor in the Departments of Computer Science and Mathematics at the University of California, Irvine. His main research interest is in 'Mathematical AI/ML for Multiscale Science', with a strong emphasis on biology.