Ehsan Dehghan-Niri
Papers
8
Total Citations
98
H-Index
4
About
Ehsan Dehghan-Niri is a pioneering researcher at the intersection of bio-inspired robotics, nondestructive evaluation (NDE), and deep learning. His work is defined by two compelling threads: drawing inspiration from nature’s most unusual sensory systems and engineering intelligent robots for critical infrastructure inspection. Dehghan-Niri’s most celebrated contribution is a deep learning-based thermal imaging system for robotic harvesting of chili peppers (64 citations), which demonstrates how advanced computer vision can transform agricultural automation. He is equally renowned for his groundbreaking studies of the aye-aye’s tap-scanning behavior—a rare acoustic foraging technique—which he has modeled kinematically and replicated in biomimetic robotic systems for non-contact material testing. This bio-inspired approach has led to innovative NDE methods for wooden structures and tubular components. His work also includes an inflatable soft crawling robot for overhead power line inspection, showcasing his versatility in soft robotics. With a growing portfolio of high-impact papers, Dehghan-Niri is shaping a future where robots learn from nature’s most efficient sensing strategies to perform safer, more precise inspections across agriculture, energy, and civil infrastructure.
Research Focus
Key Achievements
Top Papers
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- 7Aye-aye’s middle finger kinematic modeling during tap-scanning2 citations · 2022
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