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About

Sourojit Saha is a leading researcher in robotics and autonomous systems, with a primary focus on simultaneous localization and mapping (SLAM) for challenging, all-weather environments. His most impactful contribution is the creation of the SubT-MRS Dataset (2024, 46 citations), a pioneering benchmark designed to push SLAM algorithms toward sustained performance in degraded visual conditions. This work directly addresses a critical gap in the field: while numerous SLAM datasets exist, most fail to test resilience under adverse weather, low light, or subterranean settings. By providing multimodal sensor data from real-world underground and surface environments, Saha’s dataset has become an essential resource for developing more robust navigation systems for autonomous exploration, search-and-rescue, and planetary rovers. His research bridges the gap between controlled lab experiments and real-world deployment, earning recognition for advancing the reliability of autonomous platforms. Saha’s contributions are shaping the next generation of SLAM solutions that can operate reliably in the unpredictable conditions where they are needed most.