**PAPERS** · CV

Delay-coordinate maps, coherence, and approximate spectra of evolution operators

D. Giannakis (2020), arXiv:2007.02195

Kernel analog forecasting: Multiscale test problems

D. Burov, D. Giannakis, K. Manohar, A. M. Stuart (2020), arXiv:2005.06623

Koopman spectra in reproducing kernel Hilbert spaces

S. Das, D. Giannakis (2020), *Appl. Comput. Harmon. Anal.*, 49, 573–607

An information-geometric approach to feature extraction and moment reconstruction in dynamical systems

S. Das, D. Giannakis, E. Szekely (2020), arXiv:2004.02172

Operator-theoretic framework for forecasting nonlinear time series with kernel analog techniques

R. Alexander, D. Giannakis (2020), *Phys. D*, 409, 132520

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

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

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)