Sukanya Nag

National Institute of Technology Agartala

Papers

Total Citations

H-Index

About

Sukanya Nag is a researcher at the intersection of computer vision, image processing, and digital fabrication. Her primary research focuses on developing novel methods for edge detection and vectorization, specifically tailored for robotic and CNC-based artistic production. Nag’s major contribution lies in bridging the gap between digital image analysis and physical manufacturing: she pioneered a multi-stage edge detection framework that converts raster images into precise vector paths, enabling robotic arms and CNC machines to faithfully reproduce artworks. Her work on deploying fractal geometries—including the Sierpinski gasket, Barnsley fern, and Koch snowflake—through CNC devices demonstrates how mathematical patterns can be translated into tangible, machined objects. While her most-cited papers currently hold 2 citations each, they represent foundational steps in a niche but growing field of computational creativity and automated fabrication. Nag’s research is particularly notable for its practical application: her vectorization pipeline directly feeds into industrial vector devices, making her work relevant for artists, engineers, and hobbyists seeking to automate the reproduction of complex imagery. Her achievements include successfully demonstrating the first end-to-end system for fractal propagation on CNC routers, opening new avenues for algorithmic art and precision manufacturing.