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About

Dharam Buddhi is a prominent researcher whose work sits at the intersection of robotics, automation, and intelligent systems engineering. His scholarship spans collaborative robotics, structural optimization, assistive technologies, and biomedical micromanipulation — areas where he has made notable strides in advancing both theoretical foundations and practical applications. Buddhi's most cited contribution, "Robust deflection control and analysis of a fishing rod-type flexible robotic manipulator" (2022, 69 citations), demonstrates his expertise in designing adaptive robotic systems for collaborative environments. Complementing this, his development of hybrid optimization methodologies — combining finite element methods, neural-fuzzy systems, and bio-inspired algorithms like the water cycle–moth flame approach — reflects a sophisticated, multidisciplinary approach to mechanical design challenges in robotics manufacturing. His work extends meaningfully into human-centered technologies, including the Caster Walker GAIT Trainer, a robotic assistive device aimed at mobility rehabilitation, and context-aware frameworks for defense-oriented cobots leveraging ontological and deep learning models. In biomedical engineering, his topology-optimized robotic graspers and 3D-printed grippers for micromanipulation address critical challenges in handling delicate biological specimens. Collectively, Buddhi's research represents a forward-thinking fusion of intelligent computation and real-world robotic application.