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About

Yashwanth Bandari is a researcher specializing in robotic additive manufacturing, advanced sensing systems, and process optimization for large-scale metal fabrication. His work sits at a compelling intersection of robotics, manufacturing automation, and materials engineering, addressing practical challenges that hinder the widespread adoption of next-generation fabrication technologies. Bandari's most significant contributions include pioneering comparative analyses of robotic versus CNC systems for large-scale additive manufacturing, arguing persuasively for robotic approaches due to their cost-effectiveness and configurational flexibility — a paper that has attracted 25 citations. Equally influential is his development of a non-contact laser speckle sensor for measuring robotic tool speed, also garnering 25 citations, demonstrating his versatility across hardware innovation and software-driven solutions. His work on motion error compensation strategies (14 citations) further advances the reliability of robotic additive manufacturing systems. Bandari has also made meaningful contributions to metal additive manufacturing through his investigations into Laser Metal Deposition with wire (LMD-w), examining how inter-layer cooling times affect distortion and mechanical properties — research with direct implications for aerospace manufacturing. Collectively, his publications reflect a researcher dedicated to making advanced manufacturing systems more precise, accessible, and industrially viable.