Nazila Fough

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About

Nazila Fough is a leading researcher in underwater robotics and autonomous systems, with a primary focus on advancing the Internet of Underwater Things (IoUT) for critical infrastructure monitoring. Her most cited work, "Towards the underwater internet of things for subsea oil and gas monitoring" (2025, 11 citations), lays foundational frameworks for integrating smart sensors and communication networks into subsea environments, enabling real-time, remote oversight of oil and gas operations. Fough’s research addresses the formidable challenges of subsea robotic vision—including non-uniform light attenuation, backscattering, and low-light conditions—that degrade image quality and impede autonomous navigation. In her notable study "Promptable Sonar Image Segmentation for Distance Measurement Using SAM" (2024, 5 citations), she introduces a novel approach leveraging the Segment Anything Model (SAM) for promptable segmentation of sonar imagery, enabling precise distance measurement in murky waters. This work directly enhances the reliability of robotic operations in visually degraded subsea settings. With a growing citation record reflecting the urgency of her contributions, Fough is shaping the future of autonomous underwater inspection, maintenance, and environmental monitoring. Her achievements are pivotal for students and researchers exploring resilient perception systems in extreme aquatic environments.