Anja Sheppard

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About

Anja Sheppard is an emerging researcher at the intersection of machine learning and robotic perception, with a particular focus on enabling autonomous systems to operate in challenging and extreme environments. Her work addresses a critical gap in underwater and subsurface sensing, developing novel approaches that extend machine learning capabilities beyond conventional terrestrial applications. Sheppard's most notable contribution is her benchmark dataset for shipwreck segmentation from side scan sonar imagery, which has already garnered 28 citations since its 2024 publication — a remarkable achievement for such a recent work. By creating open-source, standardized datasets for underwater acoustic imaging, she is actively lowering barriers for the broader research community to develop and validate state-of-the-art perception algorithms. Complementing this, her research on ground penetrating radar for terrain classification demonstrates a broader commitment to robust sensing in visually degraded conditions, directly supporting autonomous navigation and planning in environments where cameras alone fall short. Though early in her career, Sheppard's focus on benchmark creation and cross-modal sensing positions her as a valuable contributor to the field of marine and field robotics, where reliable perception remains one of the most persistent open challenges.