Niloufar Amiri
Papers
5
Total Citations
25
H-Index
3
About
Niloufar Amiri is a rising researcher at the intersection of robotics, control systems, and computer vision. Her work focuses on two primary areas: the design and motion control of energy-efficient vibration-driven robots, and the application of deep learning to visual servoing for aerial and manipulator robots. In her foundational 2023 paper on vibration-driven robots, she explored innovative mechanical systems capable of navigating complex environments for tasks like debris clearance and pipeline inspection. Her most impactful contributions, however, lie in visual servoing. Amiri has pioneered the use of self-organizing neural networks and convolutional neural networks for robust, keypoint-based visual control of aerial robots, as demonstrated in her 2024 and 2025 papers. Her 2024 work on keypoint detection for manipulators further advances the field of deep visual servoing. With over 25 citations across her top five papers, Amiri is establishing herself as a key voice in intelligent robotic control, bridging the gap between classical control theory and modern deep learning for real-world robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Optimization and control of an energy-efficient vibration-driven robot9 citations · 2023
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