PeopleofSuperintelligence

Researcher

J. Nathan Kutz

Also known as José Nathan Kutz, Nathan Kutz

J. Nathan Kutz is an applied mathematician who works where machine learning meets dynamical systems, and he directs physics-informed AI at Autodesk Research in London. After a physics and mathematics degree at the University of Washington and a 1994 PhD in applied mathematics at Northwestern, he joined the UW faculty in 1998 and chaired its applied mathematics department from 2007 to 2015. With Steven Brunton and Joshua Proctor, he coauthored a 2015 method that uses sparse regression and machine learning to discover governing equations from measurement data, and he wrote the 2019 textbook Data-Driven Science and Engineering with Brunton. He became director of the NSF-funded AI Institute in Dynamic Systems in 2021 and a SIAM Fellow in 2022, and he is on leave from UW, where he is the Boeing Professor of Applied Mathematics and Electrical and Computer Engineering.

Timeline

  1. 1990–1997

    A Northwestern PhD and postdocs

    He earns a B.S. in physics and mathematics at the University of Washington in 1990 and a PhD in applied mathematics at Northwestern University in 1994, advised by William Kath. He then holds postdoctoral fellowships at the Institute for Mathematics and its Applications at the University of Minnesota from 1994 to 1995 and at Princeton University from 1995 to 1997.

  2. 1998–2015

    Professor and chair at UW

    He joins the University of Washington faculty in 1998 and chairs its Department of Applied Mathematics from 2007 to 2015. His research covers nonlinear waves and coherent structures, especially in fiber lasers, along with dimensionality reduction and data analysis for complex systems.

  3. 2012–2013

    A Radcliffe fellowship

    He spends 2012–2013 as a fellow of Harvard's Radcliffe Institute for Advanced Study, where he develops a biologically inspired mathematical framework for sensory and pattern-recognition systems while holding UW's Robert Bolles and Yasuko Endo Professorship. In 2013, Oxford University Press publishes his book Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data.

  4. 2015–2019

    Learning governing equations from data

    In 2015, he coauthors a method for the sparse identification of nonlinear dynamical systems with Steven Brunton and Joshua Proctor; it combines sparse regression and machine learning to discover governing equations from measurement data. He coauthors the 2016 SIAM book Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems. In 2019, Cambridge University Press publishes Data-Driven Science and Engineering, his textbook with Brunton that joins machine learning, engineering mathematics and mathematical physics.

  5. 2021

    Directing an NSF AI institute

    In July 2021, the National Science Foundation names the UW-led AI Institute in Dynamic Systems among 11 new AI research institutes, each funded with about $20 million over five years. Kutz is its director and Steve Brunton its associate director; launched in October 2021, the institute pairs physics-based models with machine learning for real-time learning and control of complex dynamic systems such as turbulence.

  6. 2022

    A SIAM fellowship

    He is elected a Fellow of the Society for Industrial and Applied Mathematics in 2022 for contributions to applied dynamical systems, machine learning and nonlinear optics.

  7. 2023

    Nelder lectures at Imperial

    From November 2023 to December 2023, he gives a series of four Nelder lectures at Imperial College London on data-driven modeling of dynamical systems. The course covers dynamic mode decomposition, sparse identification of nonlinear dynamics and neural networks, implemented in Python with pyDMD, pySINDy and PyTorch.

  8. As of October 2026

    Physics-informed AI at Autodesk

    He leads the physics-informed AI group at Autodesk Research's London office and is on leave from UW, where he is the Boeing Professor of Applied Mathematics and Electrical and Computer Engineering. His group builds physics-constrained algorithms to improve generative design and digital twin accuracy in Autodesk products. In February 2026, he traces the move to a London sabbatical with the McLaren Formula 1 team and describes his aim of combining physics-informed AI with Autodesk's design ecosystem to compress design cycles.

  1. Google had the most people shaping AI every year from 2014 to 2025Our estimates of which organizations employed the most people shaping AI from 1961 to 2025, with a year-by-year chart.
  2. The United States employs an estimated 53% of people in our data with a known employment countryOur estimates of where AI careers are concentrated now and how countries’ shares of dated positions changed over time.
  3. 46% of living people in our data with known birth and employment countries work outside their birth countryOur estimate of cross-border careers in AI, from country of birth and the country of each current organization.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionOur estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

Sources and credits

Photo: We have no published photo of J. Nathan Kutz yet. Send us a free-licensed photo.

  1. Jose Nathan Kutz | UW Department of Electrical & Computer Engineering people.ece.uw.edu. Checked 19 October 2026.
  2. J. Nathan Kutz - Wikipedia en.wikipedia.org. Checked 19 October 2026.
  3. J. Nathan Kutz | Radcliffe Institute for Advanced Study at Harvard University radcliffe.harvard.edu. Checked 19 October 2026.
  4. [1509.03580] Discovering governing equations from data: Sparse identification of nonlinear dynamical systems arxiv.org. Checked 19 October 2026.
  5. J. Nathan Kutz | Department of Applied Mathematics | University of Washington amath.washington.edu. Checked 19 October 2026.
  6. Data-Driven Science and Engineering cambridge.org. Checked 19 October 2026.
  7. UW to lead new NSF institute for using artificial intelligence to understand dynamic systems | UW News washington.edu. Checked 19 October 2026.
  8. AI for engineering | UW Department of Electrical & Computer Engineering ece.uw.edu. Checked 19 October 2026.
  9. Professor Nathan Kutz elected SIAM fellow | Department of Applied Mathematics | University of Washington amath.washington.edu. Checked 19 October 2026.
  10. Nelder Lecture Series – Prof Nathan Kutz: Data-driven modeling of dynamical systems | Events | Imperial College London imperial.ac.uk. Checked 19 October 2026.
  11. Nathan Kutz | Autodesk Research research.autodesk.com. Checked 19 October 2026.
  12. AMMCS 2026 | Closing the gap between physical reality and the world of simulation ammcs.wlu.ca. Checked 19 October 2026.
  13. Advancing Physics-Informed AI at Autodesk: A Conversation with Nathan Kutz research.autodesk.com. Checked 19 October 2026.