Data-Driven Participation Factors for Nonlinear Systems Based on Koopman Mode Decomposition. - Marcos Netto; Yoshihiko Susuki; Lamine Mili (IEEE Control. Syst. Lett., 2019)

NREL 30-Second ASI Timeseries April 4-21, 2019. - Peter Shaffery; Afshin Andreas; Manajit Sengupta; Aron Habte; Marcos Netto; Venkat Krishnan (IEEE DataPort, 2020)

A robust extended Kalman filter for power system dynamic state estimation using PMU measurements. - Marcos Netto; Junbo Zhao 001; Lamine Mili (CoRR, 2021)

Measurement placement in electric power transmission and distribution grids: Review of methods and opportunities. - Marcos Netto; Venkat Krishnan; Yingchen Zhang; Lamine Mili (CoRR, 2021)

On Analytical Construction of Observable Functions in Extended Dynamic Mode Decomposition for Nonlinear Estimation and Prediction. - Marcos Netto; Yoshihiko Susuki; Venkat Krishnan; Yingchen Zhang (IEEE Control. Syst. Lett., 2021)

Robust Dynamic Mode Decomposition. - Amir Hossein Abolmasoumi; Marcos Netto; Lamine Mili (IEEE Access, 2022)

A mode-in-state contribution factor based on Koopman operator and its application to power system analysis. - Kenji Takamichi; Yoshihiko Susuki; Marcos Netto; Atsushi Ishigame (CoRR, 2022)

Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model. - Yijun Xu 001; Marcos Netto; Lamine Mili (CoRR, 2023)

Statistical analysis and method to quantify the impact of measurement uncertainty on dynamic mode decomposition. - Pooja Algikar; Pranav Sharma; Marcos Netto; Lamine Mili (CDC, 2024)

Participation Factors for Nonlinear Autonomous Dynamical Systems in the Koopman Operator Framework. - Kenji Takamichi; Yoshihiko Susuki; Marcos Netto (CoRR, 2024)

Efficient streaming dynamic mode decomposition. - Aditya Kale; Marcos Netto; Xinyang Zhou (CoRR, 2025)