Papers
12
Total Citations
122
H-Index
6
About
Annette Stahl is a prominent researcher at the intersection of marine robotics, computer vision, and autonomous systems, with a particular focus on underwater applications spanning aquaculture, ocean observation, and archaeological documentation. Her work addresses some of the most pressing challenges in deploying intelligent robotic systems in complex underwater environments. Stahl's most cited contribution, "Vision-based pose estimation for autonomous operations in aquacultural fish farms" (2021, 29 citations), demonstrates her leadership in developing safer, automated alternatives to human diving operations. Her innovative work on robot imitation learning in virtual reality (2018, 24 citations) showcases a creative approach to training robotic fish-handling systems without requiring direct physical experimentation. She has also advanced ocean ecosystem monitoring through AI-driven mobile explorers capable of plankton classification and unsupervised species discovery, contributing meaningfully to marine ecology research. More recently, Stahl has expanded into 3D scene reconstruction, including neural radiance field-based RGB-D mapping and mesh analysis for underwater heritage sites. Her aquaculture contributions extend to net integrity monitoring through automated hole detection, addressing real-world salmon farming challenges. With over 110 cumulative citations across diverse domains, Stahl's research consistently bridges fundamental computer vision methods with high-impact marine and industrial applications.
Research Focus
Key Achievements
Top Papers
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- 3Advancing Ocean Observation with an AI-Driven Mobile Robotic Explorer16 citations · 2020
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- 5Hole detection in aquaculture net cages from video footage8 citations · 2022
- 6RGB-D Mapping and Tracking in a Plenoxel Radiance Field7 citations · 2024
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