Why I Strongly Recommend Steven Brunton’s Books and Lectures

Today I want to highlight the work of Prof. Steven L. Brunton, a leading researcher and educator in data-driven modeling, control, and machine learning for dynamical systems. He is a Professor of Mechanical Engineering at the University of Washington, with adjunct appointments in Aeronautics & Astronautics, Computer Science, and Applied Mathematics. His interdisciplinary background—combined with a Ph.D. from Princeton University in Mechanical and Aerospace Engineering—makes his teaching and research uniquely broad, rigorous, and accessible.

Prof. Brunton is widely known for his outstanding books and lecture series on machine learning, control, and modern dynamical systems. His textbooks, such as Data-Driven Science and Engineering and Modern Data-Driven Modeling and Control (co-authored with J. N. Kutz), provide exceptionally clear explanations of topics including sparse regression, system identification, Koopman operator theory, reduced-order modeling, and optimal control. These books have become foundational references for students and researchers working at the intersection of engineering, data science, and control theory.

Equally impressive is his extensive collection of educational videos. His YouTube lectures cover machine learning for engineers, system identification, control theory, SVD and PCA, compressive sensing, nonlinear dynamics, and fluid mechanics. The clarity of his explanations, the mathematical intuition he provides, and the way he connects theory to real engineering applications make his content valuable for anyone learning modern modeling and control.

I personally find his teaching incredibly helpful, and I strongly encourage my future students—and anyone working in engineering, robotics, or data-driven modeling—to explore his books and video lectures. Whether you are learning machine learning for the first time or aiming to understand advanced techniques like Koopman analysis or sparse identification of nonlinear dynamics (SINDy), his materials are among the best resources available.

You can explore his educational videos here:
https://www.youtube.com/@Eigensteve

His books can be found here:
https://www.databookuw.com/