Research Interests
My research centers on applying deep learning—especially Mamba and Transformer-based architectures—to satellite image processing for geographic applications such as disaster management, environmental monitoring, and land use change detection. I focus on tasks like speckle noise denoising and segmentation to enhance the analysis of complex geospatial data. Building on this foundation, I aim to expand into video analysis to support spatiotemporal monitoring, including urban growth, deforestation, and infrastructure development. By adapting these models for high-dimensional and time-series data, my work advances geospatial intelligence and supports decision-making in dynamic geographic environments through an interdisciplinary deep learning approach.
Education
- Master of Environmental Studies, MES, University of Waterloo, 06/2025
- Master of Management Innovation & Entrepreneurship, Queen’s University, 08/2022
- Certificate in Urban Planning, Queen’s University, 04/2021
- B.A. Honours in Geography, Queen’s University, 04/2021