Saumil Jariwala

Narsee Monjee Institute of Management Studies

Papers

Total Citations

H-Index

About

Saumil Jariwala is a researcher specializing in the intersection of robotics and machine learning, with a focus on developing intelligent systems for autonomous manipulation. His most-cited work, "Robotic Hand-Eye System Using Machine Learning" (2019), introduces a novel approach that leverages machine learning algorithms to enhance the coordination between robotic vision and manipulation, enabling more precise and adaptive hand-eye control. This contribution addresses a critical challenge in robotics—bridging perception and action—by allowing robots to learn from visual feedback and adjust their movements in real time. Although his citation count is currently modest (2 citations), the foundational nature of this work signals potential for growth as the field advances. Jariwala’s research is particularly relevant for applications in manufacturing, healthcare, and service robotics, where robust hand-eye coordination is essential. His work exemplifies a hands-on, experimental methodology, combining theoretical insights with practical system design. For students and researchers exploring robotic vision or machine learning integration, Jariwala’s paper offers a clear, accessible entry point into building adaptive robotic systems.