Scholar
J. Nathan Kutz
Google Scholar ID: kfT42KEAAAAJ
Professor of Applied Mathematics & Electrical and Computer Engineering
Citations & Impact
Citations
41,971
H-index
80
i10-index
262
Publications
20
Co-authors
23
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published numerous research papers on topics such as deep learning for universal linear embeddings of nonlinear dynamics, insect cyborgs improving machine learning accuracy on limited data, etc.; involved in various research projects like light bullet generation in waveguide arrays, retinal waves on starburst amacrine cells, etc.
Research Experience
- Serves as the head of the Kutz Research Group, with extensive research experience across multiple disciplines including Applied Mathematics (AMATH), Electrical and Computer Engineering (ECE), and Mechanical Engineering.
Education
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Background
- Research interests include sparsity and dynamics, dynamic mode decomposition, machine learning, reduced-order models, etc.; professional fields cover computational neuroscience, optics, computer vision, sensor technology, and fluid dynamics.
Miscellany
- Has a particular interest in using lightboard technology to improve online education; also, a key member of a $20M AI Institute led by the University of Washington.
