My previous experience includes the development, implementation, and optimization of machine learning-based algorithms for processing remote sensing images to extract useful information through image segmentation, classification, and change detection. I have also been involved in the development, implementation, and optimization of algorithms for satellite systems. My previous research has mainly focused on synthetic aperture radar (SAR) satellites and SAR image processing. Currently, as a postdoctoral fellow, I am focused on developing machine learning methods for kelp mapping. I am working on creating software that leverages deep learning approaches to determine the aerial extent of floating kelp using optical satellite images. The software, called Satellite-based Kelp Mapping (SKeMa), will be primarily used by the First Nations in British Columbia to monitor kelp in their marine Traditional Territories.