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About

Sameer Gupta is a researcher at the intersection of evolutionary robotics and hybrid manipulator design, with a focus on modular, data-driven synthesis for customized robotic systems. His major contributions include a novel modular approach for kinematic modeling and analysis of planar hybrid manipulators, which enables rapid configuration selection for specific applications—a critical challenge in data-driven synthesis. He has also developed strategies for generating initial populations of diverse hybrid morphologies with fixed degrees of freedom, advancing the evolution of planar hybrid manipulators. His most cited work, "Evolutionary Robotics in Two Decades: A Review" (2015, 9 citations), provides a comprehensive overview of the field's progress, serving as a key reference for researchers. Additionally, his 2021 paper on task-based dimensional synthesis of an upper-limb exoskeleton in a hybrid configuration demonstrates practical applications in assistive robotics. With a total of 20 citations across his top papers, Gupta’s work is foundational for those exploring evolutionary optimization and hybrid robot design, offering both theoretical frameworks and actionable methodologies for students and engineers alike.