PAPERS · CV

Bridging data science and dynamical systems theory
T. Berry, D. Giannakis, J. Harlim (2020), arXiv:2002.07928

Spectral exterior calculus
T. Berry, D. Giannakis (2020), Commun. Pure Appl. Math., 73, 0689-0770

Extended-range statistical ENSO prediction through operator-theoretic techniques for nonlinear dynamics
X. Wang, J. Slawinska, D. Giannakis (2020), Sci. Rep, 10, 2636

Extraction and prediction of coherent patterns in incompressible flows through space-time Koopman analysis
D. Giannakis, S. Das (2020), Phys. D, 402, 132211

Quantum dynamics of the classical harmonic oscillator
D. Giannakis (2019), arXiv:1912.12334

Reproducing kernel Hilbert algebras on compact Lie groups
S. Das, D. Giannakis (2019), arXiv:1912.11664

Quantum mechanics and data assimilation
D. Giannakis (2019), Phys. Rev. E, 100, 032207

Spatiotemporal pattern extraction by spectral analysis of vector-valued observables
D. Giannakis, A. Ourmazd, J. Slawinska, Z. Zhao (2019), J. Nonlinear Sci., 29(5), 2385-2445

Data-driven spectral decomposition and forecasting of ergodic dynamical systems
D. Giannakis (2019), Appl. Comput. Harmon. Anal., 62(2), 338-396

Galerkin approximation of dynamical quantities using trajectory data
E. Thiede, D. Giannakis, A. R. Dinner, J. Weare (2019), J. Chem. Phys., 150, 244111

Operator-theoretic framework for forecasting nonlinear time series with kernel analog techniques
R. Alexander, D. Giannakis (2019), arXiv:1906.00464

A quantum mechanical approach for data assimilation in climate dynamics
J. Slawinska, A. Ourmazd, D. Giannakis (2019), ICML 2019 Workshop on "Climate Change: How Can AI Help?"

Delay-coordinate maps and the spectra of Koopman operators
S. Das, D. Giannakis (2019), J. Stat. Phys., 175(6), 1107-1145

Predicting regional and pan-Arctic sea ice anomalies with kernel analog forecasting
D. Comeau, D. Giannakis, Z. Zhao, A. J. Majda (2019), Climate Dyn., 52(9-10), 5507-5525

The Antarctic circumpolar wave and its seasonality: Intrinsic traveling modes and ENSO teleconnections
X. Wang, D. Giannakis, J. Slawinska (2019), Int. J. Climatol., 39(2), 1026-1040

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

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

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 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)