Regular biography
Kathrin Hellmuth is a von Karman Instructor in Computing and Mathematical Sciences at the California Institute of Technology, affiliated with the CS department. She holds a B.S. from Julius-Maximilians University of Wurzburg, completed her M.S. in 2020, and earned her Ph.D. in 2025. Hellmuth's research interests are not explicitly detailed in the provided information. She teaches CMS/ACM/IDS 107 ab – Linear Analysis with Applications during the 2025-26 academic year. Her profile page provides additional details on her publications and related courses.
Scholar-generated biography
Kathrin Hellmuth von Karman is an instructor at the California Institute of Technology (Caltech) whose research focuses on mathematical modeling of biological and financial systems. Her work explores inverse problems in partial differential equations (PDEs), particularly in the context of chemotaxis and bacterial movement. She investigates the kinetic chemotaxis kernel, its reconstruction from macroscopic data, and the well-posedness of related inverse problems. Her research also extends to machine learning applications in financial modeling, such as solving the Black Scholes equation with uncertain volatility. Additionally, she examines experimental design for PDE parameter identification and the sensitivity of Fisher Information Matrix through random data down-sampling.