George Pasparakis

Past Research Group members

George received his Ph.D. degree in 2022 from Leibniz University Hannover, Germany, under the co-supervision of Prof. Beer and Prof. Kougioumtzoglou.

Dissertation: Sparse Representations and Harmonic Wavelets for Stochastic Modeling and Analysis of Diverse Structural Systems and Related Excitations

Current Position: Machine Learning Researcher, Bayer R&D, USA

Publications

Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods

George D. Pasparakis

Ketson R. M. dos Santos

Ioannis A. Kougioumtzoglou

Michael Beer

Excitation–response relationships for linear structural systems with singular parameter matrices: A periodized harmonic wavelet perspective

George P. Pasparakis

Ioannis A. Kougioumtzoglou

Vasileios C. Fragkoulis

Fan Kong

Michael Beer

On the efficacy of sparse representation approaches for determining nonlinear structural system equations of motion

George D. Pasparakis

Vasileios C. Fragkoulis

Ioannis A. Kougioumtzoglou

Joint space–time wind field data extrapolation and uncertainty quantification using nonparametric Bayesian dictionary learning

George D. Pasparakis

Ioannis A. Kougioumtzoglou

Michael D. Shields

Publications

Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods

Excitation–response relationships for linear structural systems with singular parameter matrices: A periodized harmonic wavelet perspective

On the efficacy of sparse representation approaches for determining nonlinear structural system equations of motion

Joint space–time wind field data extrapolation and uncertainty quantification using nonparametric Bayesian dictionary learning

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