Elis Trindade
Visiting Researcher (PhD Candidate)
Elis Trindade is a Visiting Research Student at Simon Fraser University and a Ph.D. candidate in Electrical Engineering at São Paulo State University (UNESP), Brazil. She holds both a B.Sc. and an M.Sc. in Electrical Engineering.
Her research focuses on fault detection, classification, and location in active power distribution systems, with an emphasis on data-driven and intelligent approaches for power system protection. Her work involves machine learning techniques, including adaptive neuro-fuzzy inference systems and graph-based learning methods, to improve fault diagnosis under different operating conditions.
During her research period at SFU, she is working on the development and evaluation of data-driven approaches for fault diagnosis in active power distribution systems. Her research aims to extend machine-learning-based methodologies, including graph neural networks, to more realistic operating scenarios, such as distribution networks with distributed energy resources and limited measurement availability, and to investigate their implementation and validation using real-time simulation environments. Her broader research interests include power system protection, active distribution networks, distributed energy resources, artificial intelligence, and machine learning applications in power systems..