- Ph.D. in Mechanical and Aerospace Engineering, Princeton University, 2012
- B.S. in Mathematics, Minor in Control and Dynamical Systems, California Institute of Technology, 2006
- Assistant Professor, Mechanical Engineering, University of Washington, 2014
- Acting Assistant Professor, Applied Mathematics, University of Washington, 2012–2014
Dr. Brunton's research focuses on combining techniques in dimensionality
reduction, sparse sensing, and machine learning for the data-driven
discovery and control of complex dynamical systems. He is also
interested in how low-rank coherent patterns that underlie
high-dimensional data facilitate sparse measurements and optimal sensor
and actuator placement for control. He is developing adaptive
controllers in an equation-free context using machine learning. Specific
applications in fluid dynamics include closed-loop turbulence control
for mixing enhancement, bio-locomotion, and renewable energy. Other
applications include neuroscience, medical data analysis, networked
dynamical systems, and optical systems.
- Brunton & Kutz. Data Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control. Cambridge 2019.
- Brunton, Noack, Koumoutsakos. Machine Learning for Fluid Mechanics. Annual Review of Fluid Mechanics, 52:477–508, 2020.
- Brunton, Proctor, Kutz. Discovering governing equations from data by sparse identification of nonlinear dynamical systems. Proceedings of the National Academy of Sciences, 113(15):3932—3937, 2016.
- Kutz, Brunton, Brunton, Proctor. Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems. Part of the Other Titles in Applied Mathematics, volume 148, Society for Industrial and Applied Mathematics, 2016.
- Brunton & Noack. Closed-loop turbulence control: Progress and challenges. Applied Mechanics Reviews, 67(5):050801-1—050801-48, 2015.
With over four million views and 90,000 subscribers, Professor Steve Brunton’s YouTube channel simplifies the mathematical fundamentals behind data-driven engineering concepts.
Brunton receives the PECASE
Associate professor Steve Brunton receives the Presidential Early Career Award for Scientists and Engineers (PECASE).
Big data and automation
These ME research projects demonstrate how mechanical engineers are expanding future applications of machine learning.