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About

Ashish Kulkarni is a leading researcher at the intersection of robotics and advanced manufacturing, whose work is redefining how complex parts are built. His primary research areas include automated process planning, robotic additive manufacturing, and multi-resolution fabrication. Kulkarni’s major contributions lie in developing intelligent algorithms that optimize the entire additive manufacturing workflow—from part placement to deposition speed. Notably, his 2021 paper on "Automated Planning for Robotic Multi-Resolution Additive Manufacturing" (19 citations) introduced a groundbreaking method that intelligently balances surface quality and build time by varying bead sizes, a critical advance for industrial applications. His work on "Automated process planning for conformal wire arc additive manufacturing" (16 citations) further extends these capabilities to metal printing on curved surfaces. Kulkarni has also pioneered the use of unsupervised learning to regulate deposition speed in wire arc additive manufacturing, enhancing process stability. With a growing citation impact and a focus on practical, accuracy-driven solutions, Kulkarni is shaping the future of autonomous, high-precision digital fabrication.