Md. Ragib Shaharear

Shahjalal University of Science and Technology, Johns Hopkins University, Arizona State University

Papers

Total Citations

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About

Md. Ragib Shaharear is a robotics researcher whose work bridges autonomous systems, bio-inspired design, and efficient machine learning for embedded platforms. His most cited work, "Designing and Optimization of An Autonomous Vacuum Floor Cleaning Robot" (43 citations), addresses the growing demand for affordable home automation by developing a practical, cost-effective cleaning robot—a contribution that resonates with both academic and hobbyist communities. Shaharear also explores novel locomotion mechanisms in "Penetration Forces of a Rotating Helical Penetrator in Granular Media," where he draws inspiration from self-burial behaviors in nature (e.g., Erodium seeds, sandfish skink) to inform the design of burrowing robots, offering insights for subterranean exploration. More recently, his work "ViT-Reg: Regression-Focused Hardware-Aware Fine-Tuning for ViT on TinyML Platforms" (2024) tackles the challenge of deploying vision transformers on resource-constrained devices, providing a framework that balances accuracy and energy efficiency—a critical step toward intelligent edge computing. With a portfolio spanning autonomous navigation, bio-inspired engineering, and TinyML optimization, Shaharear’s research demonstrates a commitment to making robotics and AI more accessible, efficient, and nature-informed.