Professor, Electrical & Computer Engineering

Research focus

Data science, machine learning, scientific computing, dynamical systems, optical and atomic physics, computational neuroscience, fluid dynamics

Education

Ph.D. Applied Mathematics, Northwestern University, 1994
B.S. Physics and Mathematics, University of Washington, 1990

J. Nathan Kutz is the Robert Bolles and Yasuko Endo Professor of Applied Mathematics at the University of Washington and an adjunct professor in Mechanical Engineering. He joined Electrical & Computer Engineering in July of 2022. Among other prestigious academic and professional positions, he served as chair of Applied Mathematics from 2007 to 2015.

Kutz’s research interests broadly relate to computing and data science, including data analysis and reduced order models, dynamical systems, physic-informed machine learning, complex systems and partial differential equations, linear and nonlinear wave propagation, perturbation and asymptotic methods, bifurcation theory, scientific computing, data-driven control theory, mode-locked lasers, neuroscience, sensor networks, and fluid dynamics. His honors include being elected a Society for Industrial and Applied Mathematics Fellow, NSF CAREER Award and a Hughes Research Laboratories Research Award.