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About

Ruddra dev Roychoudhury is an emerging researcher at the intersection of embodied AI, robotic perception, and telepresence systems. His work addresses two critical challenges in robotics: enabling robots to understand and act on natural language instructions in complex environments, and creating practical systems for remote human-robot interaction. In his highly cited paper “DoRO: Disambiguation of Referred Object for Embodied Agents” (19 citations), Roychoudhury tackles the fundamental problem of grounding ambiguous task instructions—a key bottleneck in deploying robots that can follow natural language commands. His research on “Spatial Relation Graph and Graph Convolutional Network for Object Goal Navigation” (8 citations) introduces a novel graph-based framework that learns spatial relationships from trajectory histories, enabling robots to efficiently navigate toward target objects. Roychoudhury has also made significant contributions to telepresence robotics through his work on “Teledrive” (7 citations), which presents an edge-centric architecture for collaborative multi-presence scenarios. His broader perspective on the field, published in “A Perspective on Robotic Telepresence and Teleoperation using Cognition,” reflects his thoughtful approach to advancing intelligent robotic systems from laboratory demonstrations to real-world deployment.