Eila is a first-year undergraduate student in the Engineering Science program at the University of Toronto. In the ATOMS lab, Eila’s research aims to optimize wind farm efficiency through computational modeling, increasing energy production and reducing turbine wear. Her project utilizes Deep Convolutional Conditional Generative Adversarial Networks (DC-CGANs) to develop a surrogate modeling framework that predicts wake flow patterns in wind farms more accurately and swiftly than existing models