Journal Papers


  1. Frequency selection by feedback control in a turbulent shear-flow,
    V. Parezanovic, L. Cordier, T. Duriez, A. Spohn, B. R. Noack, J.-P. Bonnet, M. Segond, M. Abel, and S. L. Brunton.
    To appear in the Journal of Fluid Mechanics, 2016.
    2.
  2. Discovering governing equations from data by sparse identification of nonlinear dynamical systems,
    S. L. Brunton, J. L. Proctor, and J. N. Kutz.
    Proceedings of the National Academy of Sciences, 113(15):3932--3937, 2016.
    3.
  3. Network structure of two-dimensional decaying isotropic turbulence,
    K. Taira, A. G. Nair, and S. L. Brunton.
    Journal of Fluid Mechanics, 795(R2):1--11,2016.
    4.
  4. Finite-time Lyapunov exponents for inertial particles in an unsteady fluid,
    S. Madhavan, S. L. Brunton, and J. J. Riley.
    Physical Review E, 93:033108, 2016.
    5.
  5. Koopman invariant subspaces and finite linear representations of nonlinear dynamical systems for control,
    S. L. Brunton, B. W. Brunton, J. L. Proctor, and J. N. Kutz.
    PLoS ONE, 11(2):e0150171, 2016.
    6.
  6. Multiresolution dynamic mode decomposition,
    J. N. Kutz, X. Fu, and S. L. Brunton.
    SIAM Journal on Applied Dynamical Systems, 15(2):713--735, 2016.
    7.
  7. Dynamic mode decomposition with control,
    J. L. Proctor, S. L. Brunton, and J. N. Kutz.
    SIAM Journal on Applied Dynamical Systems, 15(1):142--161, 2016.
    8.
  8. Compressive sampling and dynamic mode decomposition,
    S. L. Brunton, J. L. Proctor, and J. N. Kutz.
    To appear in the Journal of Computational Dynamics, 2016.
    9.
  9. Extremum-seeking control of the beam pattern of a reconfigurable holographic metamaterial antenna,
    M. C. Johnson, S. L. Brunton, N. B. Kundtz, and J. N. Kutz.
    Journal of the Optical Society of America A, 33(1):59--68, 2016.
    10.
  10. Intelligent systems for stabilizing mode-locked lasers and frequency combs: Machine learning and equation-free control paradigms for self-tuning optics,
    J. N. Kutz, and S. L. Brunton.
    Nanophotonics, 4(1):459--471, 2015.
    11.
  11. Nonlinear model reduction for dynamical systems using sparse sensor locations from learned libraries,
    S. Sargsyan, S. L. Brunton, and J. N. Kutz.
    Physical Review E, 92(3), 033304, 2015.

  12. Closed-Loop Turbulence Control: Progress and Challenges,
    S. L. Brunton and B. R. Noack.
    Applied Mechanics Reviews, 67(5), 050801, 2015.
    13. http://dx.doi.org/10.1115/1.4031175

  13. Sidelobe canceling for optimization of reconfigurable holographic metamaterial antenna,
    M. C. Johnson, S. L. Brunton, J. N. Kutz, and N. B. Kundtz.
    IEEE Transactions on Antennas and Propagation, 63(4):1881--1886, 2015.
    14.  [PDF]

  14. Mixing layer manipulation experiment: From open-loop forcing to closed-loop machine learning turbulence control,
    V. Parezanovic, J.-C. Laurentie, J. Delville, L. Cordier, C. Fourment, A. Spohn, B. R. Noack, J.-P. Bonnet, T. Shaqarin, M. Segond, M. Abel, and S. L. Brunton.
    The Journal of Flow, Turbulence and Combustion, 94(1):155-173, 2015.
    15.  [PDF]

  15. Compressive sensing and low-rank libraries for classification and reconstruction of nonlinear dynamical systems,
    S. L. Brunton, J. H. Tu, I. Bright, and J. N. Kutz.
    SIAM Journal on Applied Dynamical Systems, 13(4):1716-1732, 2014.
    16.  [PDF]

  16. Exploiting sparsity and equation-free architectures in complex systems,
    J. L. Proctor, S. L. Brunton, B. W. Brunton, and J. N. Kutz,
    For special issue of the European Physical Journal Special Topics, 223:2665-2684, 2014.
    17.  [PDF]

  17. Generalizing dynamic mode decomposition to a larger class of datasets,
    J. H. Tu, C. W. Rowley, D. M. Luchtenburg, S. L. Brunton, and J. N. Kutz.
    Journal of Computational Dynamics1(2):391-421, 2014.
    18.  [PDF]

  18. Self-tuning fiber lasers,
    S. L. Brunton, X. Fu, and J. N. Kutz.
    IEEE Journal of Special Topics in Quantum Electronics 20:5, 2014.
    19.  [PDF]

  19. State-space identification of reduced-order unsteady aerodynamic models for feedback control,
    S. L. Brunton, S. T. M. Dawson, and C. W. Rowley.
    Journal of Fluids and Structures online, 2014.
    20.  [PDF]

  20. Long-time uncertainty propagation using generalized polynomial chaos and flow map composition,
    D. M. Luchtenburg, S. L. Brunton, and C. W. Rowley.
    Journal of Computational Physics 274: 783-802, 2014.
    21.  [PDF]

  21. Classification of birefringence in mode-locked fiber lasers using machine learning and sparse representation,
    X. Fu, S. L. Brunton, and J. N. Kutz.
    Optics Express 22:7 8585-8597, 2014.
    22.  [PDF]

  22. Extremum-seeking control of a mode-locked laser,
    S. L. Brunton, X. Fu, and J. N. Kutz.
    IEEE Journal of Quantum Electronics 49:10 852-861, 2013.
    23.  [PDF]

  23. Reduced-order unsteady aerodynamic models at low Reynolds numbers,
    S. L. Brunton, C. W. Rowley, and D. R. Williams.
    Journal of Fluid Mechanics 724 203-233, 2013.
    24.  [PDF]

  24. Empirical State-Space Representations for Theodorsen's Lift Model,
    S. L. Brunton and C. W. Rowley.
    Journal of Fluids and Structures 38 174-186, 2013.
    25.  [PDF]

  25. Maximum Power Point Tracking for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control,
    S. L. Brunton, C. W. Rowley, S. R. Kulkarni, and C. Clarkson.
    IEEE Transactions on Power Electronics 25:10, October 2010.
    26. [PDF]

  26. Fast Computation of FTLE Fields for Unsteady Flows: A Comparison of Methods.
    S. L. Brunton and C. W. Rowley.
    Chaos 20, January 2010.
    27.  [PDF]

Under Review

  1. Data-driven methods in fluid dynamics: Sparse classification from experimental data,
    Z. Bai, S. L. Brunton, B. W. Brunton, J. N. Kutz, E. Kaiser, A. Spohn, and B. R. Noack.
    Invited book chapter for Whither Turbulence and Big Data in the 21st Century, 2015.
    2.
  2. Multi-Resolution Dynamic Mode Decomposition,
    J. N. Kutz, X. Fu, and S. L. Brunton.
    3.
  3. Dynamic mode decomposition with control,
    J. L. Proctor, S. L. Brunton, and J. N. Kutz.
    4.
  4. Optimal sensor placement and enhanced sparsity for classification,
    B. W. Brunton, S. L. Brunton, J. L. Proctor, and J. N. Kutz.
    5.

Selected Conference Papers

  1. AIAA Fluid Dynamics Conference 2011
    2.
  2. AIAA Aerospace Sciences Meeting 2011
    3.
  3. AIAA Aerospace Sciences Meeting 2010
    4.
  4. AIAA Aerospace Sciences Meeting 2009
    5.
  5. AIAA Aerospace Sciences Meeting 2008
    6.
  6. IEEE Photovoltaic Specialist Conference 2009
    7.

Princeton Ph.D. Thesis, 2012

Caltech Senior Thesis, 2006