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Amir Masoud Tahvilian is a researcher specializing in robotic grinding, precision manufacturing, and process optimization. His work focuses on understanding the complex interactions between grinding tools and workpieces in automated systems, particularly under flexible robotic conditions. Tahvilian’s major contributions include pioneering experimental and finite element analyses to characterize grinding wheel grain topography and temperature distribution in the contact zone. His 2013 study on temperature and energy partition during robotic grinding, with 26 citations, provides critical insights into thermal effects that can cause workpiece damage or softening. Similarly, his 2015 confocal microscope study of grain topography, also with 26 citations, advances the understanding of tool wear and surface integrity. Tahvilian further developed force models for impact cutting with flexible tool holders, enhancing predictive capabilities for robotic grinding processes. His work bridges experimental validation and simulation, offering practical guidance for improving efficiency and quality in automated finishing operations. With a cumulative citation count exceeding 60, Tahvilian’s research is essential reading for engineers and researchers working on robotic machining, thermal management, and surface engineering.