At Atlar Innovation, I develop and optimize computer vision and image processing algorithms for automated satellite detection and tracking. I work on astronomical image sequences, including source detection, motion identification, and celestial position determination.
I develop and validate solutions for LEO, MEO, and GEO orbital regimes using simulated imagery and real-world data. I also improve processing modules within space surveillance pipelines, with a focus on accuracy, robustness, and computational efficiency.
In applied research projects in coastal and geospatial monitoring, I designed, implemented, and maintained image- and video-based monitoring systems for operational use. I developed algorithms to extract environmental and geospatial parameters from noisy data and applied deep learning approaches including CNN-LSTM, object detection, and semantic segmentation.
My work has also included integrating image-derived outputs into GIS platforms and spatial databases, and developing an integrated GIS system and relational database for monitoring data at the Portuguese Institute for Sea and Atmosphere (IPMA). I hold a PhD in Geosciences from the University of Aveiro, with a thesis on deep learning applications in coastal video monitoring.
