Biography

Power electronics researcher focusing on Grid-Forming/Grid-Following systems and Deep-Learning–based Grid-Impedance Estimation. Contributions include an LSTM-based R–L Estimator, the GRAND Project on Active Filtering and Energy-Storage Integration, and ongoing work with Physics-Informed Neural Networks (PINNs) for R–L Parameter Regression.

CV

Projects

Innovative methods for impedance estimation using artificial intelligence

Develop an LSTM-based model to estimate grid impedance dynamically. Learned nonlinear grid behavior from operational data without explicit equations. Improves converter control stability and fault resilience.

Grid Active Node for DC Electrical Systems (GRAND)

Development of innovative multi-port power conversion systems for DC microgrids that enable seamless integration of Distributed Energy Resources and Storage into the Internet of Energy: focus on advanced control, optimized design, and remote operability.

Contacts