Papers
2
Total Citations
22
H-Index
2
About
Sabur Baidya is a leading researcher at the intersection of Digital Twin technology, safety-critical robotics, and edge computing. His work fundamentally addresses how cyber-physical systems can achieve safe, real-time integration between virtual models and physical industrial robots. Baidya’s most cited paper, “Digital Twin in Safety-Critical Robotics Applications: Opportunities and Challenges” (2022, 16 citations), provides a foundational framework for deploying Digital Twins in high-stakes environments, highlighting both the transformative potential and the critical hurdles of IoT-driven automation. He further advances the field with “Neuro-Adaptive Dynamic Control with Edge-Computing for Collaborative Digital Twin of an Industrial Robotic Manipulator” (2023, 6 citations), where he introduces a novel neuro-adaptive control system that leverages edge computing to enable real-time, collaborative Digital Twin synchronization. This work is pivotal for enhancing communication and safety in modern manufacturing workspaces. By bridging theoretical concepts with practical, adaptive control mechanisms, Baidya is shaping the next generation of intelligent, safe, and efficient industrial automation systems.
Research Focus
Key Achievements
Top Papers
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