Nihar Masurkar
Papers
3
Total Citations
13
H-Index
3
About
Nihar Masurkar is a researcher whose work sits at the fascinating intersection of bio-inspired robotics and non-destructive industrial inspection. His research is defined by two distinct yet equally innovative threads: understanding specialized animal biomechanics and translating that knowledge into advanced robotic systems. Masurkar’s most notable contribution is his kinematic modeling of the aye-aye’s unique tap-scanning behavior (6 citations), where he analyzed the lemur’s remarkably adapted middle finger to uncover principles that could inspire future robotic sensing. In parallel, he has made significant strides in infrastructure maintenance, pioneering the integration of Electromagnetic Acoustic Transducers (EMATs) into modular robotic grippers for inspecting critical tubular components in power plants (4 citations). He has further advanced this field by applying deep learning-based time-series classification to non-contact ultrasonic testing for pipeline inspection (3 citations), demonstrating a sophisticated ability to merge machine learning with physical sensing. Masurkar’s work is notable for its creative breadth—bridging the gap between a rare primate’s evolutionary adaptation and the pressing need for safer, more efficient industrial inspection, marking him as an inventive thinker in modern robotics.
Research Focus
Key Achievements
Top Papers
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