Research

Computational Inverse Problems

My research centers on the advancement of computational techniques and relevant theory for the solution of inverse problems that arise in computationally demanding contexts such as medical and industrial imaging, as well as data science. Contemporary challenges to data science, specifically in, for example, the sub-fields of AI/ML now demand data-aware techniques to address large-scale model training and computational efficiency. As the size and complexity of data continues to grow, there is a growing need for efficient algorithms to tackle these complex problems. The focus of my research and my student's is on the integration of modern scientific computing practices with mathematically rigorous data-aware approaches to solve inverse problems.