Kamlesh Singh

Papers

Total Citations

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About

Kamlesh Singh is a researcher at the forefront of applied artificial intelligence and robotics, with a focus on creating intelligent, adaptive systems for real-world environments. His work bridges the gap between advanced computational methods and practical engineering, particularly in the domains of retail analytics and autonomous robotics. Singh’s most impactful contribution, his 2023 paper on store sales forecasting, introduces a novel fuzzy pruning least-squares support vector machine (LS-SVM) approach, a method that has already garnered 33 citations for its innovative handling of complex, non-linear data in the competitive convenience store sector. Complementing this, his 2022 study on self-adjusting robots, cited 21 times, tackles the fundamental challenge of dynamic stability by applying pendulum theory to create frameworks that autonomously reinforce their own structural integrity. This work is pivotal for advancing robust, self-correcting robotic systems. Through these contributions, Singh demonstrates a clear ability to translate theoretical models into tangible solutions for industry and automation, establishing himself as a promising voice in the integration of intelligent computation with mechanical design.