Sadman Sakib Enan
University of Minnesota, Twin Cities Orthopedics, University of Minnesota System
Papers
7
Total Citations
52
H-Index
4
About
Sadman Sakib Enan is a researcher specializing in underwater robotics, computer vision, and human-robot interaction (HRI), with a focus on enabling autonomous underwater vehicles (AUVs) to perceive and collaborate with their environments more intelligently. His most influential contribution is the development of SUIM — the first large-scale semantic segmentation dataset for underwater imagery — featuring over 1,500 pixel-annotated images across eight object categories, a benchmark that has garnered 17 citations and become a foundational resource for the underwater vision community. Complementing this, his work on deep residual network-based super-resolution (13 citations) advances the visual perception capabilities of underwater robots operating in challenging, low-clarity conditions. Enan has also made significant strides in underwater human-robot collaboration, designing gestural communication frameworks for AUV-to-AUV and diver interaction (10 citations), as well as methods for diver identification through facial recognition and anthropometric data. His contributions to the open-source LoCO AUV platform further demonstrate his commitment to accessible, practical robotics research. Collectively, his work bridges the gap between machine perception and real-world underwater autonomy, making him a notable emerging voice in marine robotics and underwater HRI research.
Research Focus
Key Achievements
Top Papers
- 1Semantic Segmentation of Underwater Imagery: Dataset and Benchmark17 citations · 2020
- 2Underwater Image Super-Resolution using Deep Residual Multipliers13 citations · 2020
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- 6Visual Diver Face Recognition for Underwater Human-Robot Interaction2 citations · 2020
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