Mohammad Shahin

The University of Texas at San Antonio, University of Tennessee at Knoxville

Papers

Total Citations

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About

Mohammad Shahin’s research lies at the intersection of robotics, computer vision, and human-AI collaboration, with a focus on creating intelligent, adaptive systems for manufacturing and automation. His most-cited work, “Robotics multi-modal recognition system via computer-based vision” (2024, 13 citations), introduces a novel framework that integrates visual data with other sensory inputs to enable robots to recognize and respond to complex environments—a foundational contribution to multi-modal perception in robotics. Building on this, his forward-looking paper “The symbiotic factory: a comprehensive framework for extending lean manufacturing to human-AI collaboration” (2026, 2 citations) proposes a visionary model where humans and AI systems work in seamless synergy, redefining lean manufacturing principles for the era of intelligent automation. Shahin’s work is notable for bridging theoretical advances with practical applications, offering a roadmap for safer, more efficient human-robot teamwork. His research, though early in its citation trajectory, has already sparked interest in both academic and industrial circles, positioning him as an emerging voice in the future of smart manufacturing and collaborative robotics.