I'm a Ph.D. student in Environmental Science & Engineering at KAUST, building AI and computer vision methods for remote sensing — spanning satellite hardware, UAV imagery, and physics-informed deep learning, with a focus on water-surface distortion removal and hyperspectral image processing.
Dario received his M.Sc. in Space Engineering from the University of Naples Federico II, Italy, in 2022, and is currently pursuing a Ph.D. in Environmental Science and Engineering at KAUST, Saudi Arabia. He has contributed to projects spanning CubeSat missions, UAV-based environmental monitoring, and synthetic dataset generation for scientific imaging applications. Before his Ph.D., he worked as a satellite operator at ICEYE in Poland, operating synthetic aperture radar (SAR) satellites.
Total: 8 · h-index: 2 · i10-index: 0
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Research spanning UAV-based coastal remote sensing, hyperspectral CubeSats, self-supervised unmixing, and ground robotics — filter by authorship role.
A lightweight, camera-agnostic CV pipeline — color transfer, illumination normalization, multi-frame averaging — that strips sun glint and caustics from UAV shallow-water footage to sharpen seabed mapping.
A self-supervised ViT that unmixes hyperspectral pixels into endmembers and abundances without ground truth — guided by SVD, k-means, and VCA priors. Up to 31% better SAD, 25% better RMSE than SOTA.
Mission overview of KAUST's hyperspectral CubeSat — the Middle East's first research-focused hyperspectral Earth-observation mission, built around the Simera HyperScape50 sensor.
A quadruped robot ("Spot") with a low-beam LIDAR estimates tree height, DBH, and crown volume across 58 urban trees — rivaling far more expensive scanning setups.
6 contributions across 4 conferences — AGU, WHISPERS, and two International Astronautical Congresses. Mostly first-author work on CubeSat operations and UAV remote sensing, plus a couple of co-authored constellation and hyperspectral papers.