PAPERS · CV · RESEARCH SUMMARY
Galerkin Approximation of Dynamical Quantities using Trajectory Data
E. Thiede, D. Giannakis, A. R. Dinner, J. Weare (2018), arXiv:1810.01841

Predicting regional and pan-Arctic sea ice anomalies with kernel analog forecasting
D. Comeau, D. Giannakis, Z. Zhao, A. J. Majda (2018), Climate Dyn., in press

The Antarctic circumpolar wave and its seasonality: Intrinsic traveling modes and ENSO teleconnections
X. Wang, D. Giannakis, J. Slawinska (2018), Int. J. Climatol., in press

Reproducing kernel Hilbert space compactification of unitary evolution groups
D. Giannakis, S. Das, J. Slawinska (2018), arXiv:1808.01515

A new approach to signal processing of spatiotemporal data
J. Slawinska, D. Giannakis, A. Ourmazd (2018), 2018 IEEE Statistical Signal Processing Workshop

Data-driven spectral decomposition of ECoG signal from an auditory oddball experiment in a marmoset monkey: Implications for EEG data in humans
N. Marrouch, H. L. Read, J. Slawinska, D. Giannakis (2018): 2018 IEEE World Congress on Computational Intelligence

Koopman analysis of the long-term evolution in a turbulent convection cell
D. Giannakis, A. Kolchinskaya, D. Krasnov, J. Schumacher (2018), J. Fluid Mech., 847, 735-767

Spectral exterior calculus
T. Berry, D. Giannakis (2018), arXiv:1802.01209

Koopman spectra in reproducing kernel Hilbert spaces
S. Das, D. Giannakis (2018), arXiv:1801.07799

Spatiotemporal pattern extraction by spectral analysis of vector-valued observables
D. Giannakis, A. Ourmazd, J. Slawinska, Z. Zhao (2018), arXiv:1711.02798

Indo-Pacific variability on seasonal to multidecadal timescales. Part II: Multiscale atmosphere-ocean linkages
D. Giannakis & J. Slawinska (2018), J. Climate, 31, 2145-2167

Vector-valued spectral analysis of space-time data
D. Giannakis, J. Slawinska, A. Ourmazd, Z. Zhao (2017), NIPS Time Series Workshop 2017

Data-driven spectral decomposition and forecasting of ergodic dynamical systems
D. Giannakis (2017), Appl. Comput. Harmon. Anal., in press

Delay-coordinate maps and the spectra of Koopman operators
S. Das, D. Giannakis (2017), arXiv:1706.08544

Extraction and prediction of coherent patterns in incompressible flows through space-time Koopman analysis
D. Giannakis, S. Das (2017), arXiv:1706.06450

Data-Driven Koopman Analysis of Tropical Climate Space-Time Variability
J. Slawinska, E. Szekely, D. Giannakis (2017), Mining Big Data in Climate and Environment, SIAM International Conference on Data Mining

Pattern extraction in dynamical systems using information geometry: application to tropical intraseasonal oscillations
E. Szekely, D. Giannakis (2017), Proceedings of the 7th International Workshop on Climate Informatics: CI 2017

Indo-Pacific variability on seasonal to multidecadal timescales. Part I: Intrinsic SST modes in models and observations
J. Slawinska & D. Giannakis (2017), J. Climate, 30, 5265-5294

Data-driven prediction strategies for low-frequency patterns of North Pacific climate variability
D. Comeau, Z. Zhao, D. Giannakis & A. J. Majda (2017), Climate Dyn., 48(5–6), 1855–1872

The seasonality and interannual variability of Arctic sea-ice reemergence
M. Bushuk & D. Giannakis (2017), J. Climate, 30, 4657-4676

Extraction and prediction of indices for monsoon intraseasonal oscillations: An approach based on nonlinear Laplacian spectral analysis
C. T. Sabeerali, R. S. Ajayamohan, D. Giannakis, A. J. Majda (2017), Climate Dyn., doi:10.1007/s00382-016-3491-y

Kernel analog forecasting of tropical intraseasonal oscillations
R. Alexander, Z. Zhao, E. Szekely, D. Giannakis (2017), J. Atmos. Sci, 74, 1321-1342

Spatiotemporal pattern extraction with data-driven Koopman operators for convectively coupled equatorial waves
J. Slawinska & D. Giannakis (2016), Proceedings of the 6th International Workshop on Climate Informatics: CI 2016

Analog forecasting with dynamics-adapted kernels
Z. Zhao & D. Giannakis (2016), Nonlinearity, 29(9), 2888-2939

Initiation and termination of intraseasonal oscillations in nonlinear Laplacian spectral analysis-based indices
E. Szekely, D. Giannakis & A. J. Majda (2016), Math. Wea. Climate Forecasting, 2(1), 1-25

Spatiotemporal feature extraction with data-driven Koopman operators
D. Giannakis, J. Slawinska & Z. Zhao (2015), J. Mach. Learn. Res. Proceedings, 44, 103-115

Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection
N. D. Brenowitz, D. Giannakis & A. J. Majda (2015), J. Comput. Phys, 315, 536-553

Sea-ice reemergence in a model hierarchy
M. Bushuk, D. Giannakis (2015), Geophys. Res. Lett., 42(13), 5337–5345
Preprint; Supporting information; Movie 1

Nonparametric forecasting of low-dimensional dynamical systems
T. Berry, D. Giannakis & J. Harlim (2015), Phys. Rev. E, 91, 032915
Movie 1, 2, 3

Dynamics-adapted cone kernels
D. Giannakis (2015), SIAM J. Appl. Dyn. Syst., 14(2), 566

Arctic sea ice reemergence: The role of large-scale oceanic and atmospheric variability
M. Bushuk, D. Giannakis & A. J. Majda (2015), J. Climate, 28, 5477-5509
Movie 1, 2, 3, 4, 5, 6, 7

Extraction and predictability of coherent intraseasonal signals in infrared brightness temperature data
E. Szekely, D. Giannakis & A. J. Majda (2014), Climate Dyn., 46(5), 1473-1502
Movie 1, 2

Predicting the cloud patterns of the Madden-Julian Oscillation through a low-order nonlinear stochastic model
N. Chen, A. J. Majda & D. Giannakis (2014), Geophys. Res. Lett., 41(15), 5612

An MCMC algorithm for parameter estimation in signals with hidden intermittent instability
N. Chen, D. Giannakis, R. Herbei & A. J. Majda (2014), SIAM/ASA J. Uncertainty Quantification, 2(1), 647

Symmetric and antisymmetric signals in MJO deep convection. Part I: Basic modes in infrared brightness temperature
Tung, W.-w., D. Giannakis & A. J. Majda (2014), J. Atmos. Sci., 71, 3302

Symmetric and antisymmetric signals in MJO deep convection. Part II: Kinematics and thermodynamics
Tung, W.-w., D. Giannakis & A. J. Majda (2014), J. Atmos. Sci., submitted

Reemergence mechanisms for North Pacific sea ice revealed through nonlinear Laplacian spectral analysis
M. Bushuk, D. Giannakis & A. J. Majda (2014), J. Climate, 27, 6265

Limits of predictability in the North Pacific sector of a comprehensive climate model
D. Giannakis & A. J. Majda (2012), Geophys. Res. Lett., 39, L24602
Auxiliary material

Nonlinear Laplacian spectral analysis: Capturing intermittent and low-frequency spatiotemporal patterns in high-dimensional data
D. Giannakis & A. J. Majda (2012), Stat. Anal. and Data Min., 6(3), 180
Movie

Hierarchical structure of the Madden-Julian Oscillation in infrared brightness temperature data revealed through nonlinear Laplacian spectral analysis
D. Giannakis, W.-w. Tung & A. J. Majda, Conference on Intelligent Data Understanding (CIDU) 2012, Boulder, Colorado, October 24-26, 2012

Information theory, model error, and predictive skill of stochastic models for complex nonlinear systems
D. Giannakis, A. J. Majda & I. Horenko (2012), Physica D, 241, 1735

Comparing low-frequency and intermittent variability in comprehensive climate models through nonlinear Laplacian spectral analysis
D. Giannakis & A. J. Majda (2012), Geophys. Res. Lett., 39, L10710
Supporting information; Movie 1, 2, 3

The symmetries of image formation by scattering. I. Theoretical framework
D. Giannakis, P. Schwander & A. Ourmazd (2012), Optics Express, 20(12), 12799
Movie

The symmetries of image formation by scattering. II. Applications
P. Schwander, C. H. Yoon, A. Ourmazd & D. Giannakis (2012), Optics Express, 20(12), 12827
Movie 1, 2, 3, 4

Quantifying the predictive skill in long-range forecasting. Part I: Coarse-grained predictions in a simple ocean model
D. Giannakis & A. J. Majda (2012), J. Climate, 25(6), 1793

Quantifying the predictive skill in long-range forecasting. Part II: Model error in coarse-grained Markov models with application to ocean-circulation regimes
D. Giannakis & A. J. Majda (2012), J. Climate, 25(6), 1814

Nonlinear Laplacian spectral analysis for time series with intermittency and low-frequency variability
D. Giannakis & A. J. Majda (2012), Proc. Natl. Acad. Sci., 109(7), 2222
Supplementary information 1 (pseudocode), 2; Movie S1, S2

Time series reconstruction via machine learning: Revealing decadal variability and intermittency in the North Pacific sector of a coupled climate model
D. Giannakis & A. J. Majda, Conference on Intelligent Data Understanding (CIDU) 2011, Mountain View, California, October 19-21, 2011

Instabilities in free-surface Hartmann flow at low magnetic Prandtl numbers
D. Giannakis, R. Rosner & P. F. Fischer (2009), J. Fluid Mech., 636, 217

A spectral Galerkin method for the coupled Orr-Sommerfeld and induction equations in free-surface MHD
D. Giannakis, P. F. Fischer & R. Rosner (2009), J. Comput. Phys., 228(4), 1188

Challenges for the kinetic unified dark matter model
D. Giannakis & W. Hu (2005), Phys. Rev. D, 72, 063502

Benchmarking and incentive regulation of quality of service: An application to the UK electricity distribution networks
D. Giannakis, T. Jamasb & M. Pollitt, Energ. Policy, 33(17), 2256 (2005)