Suyog Trivedi
Papers
1
Total Citations
9
H-Index
1
About
Suyog Trivedi’s research sits at the intersection of robotics, computer vision, and retail automation, with a focus on transforming physical store operations through intelligent systems. His most cited work, “Combination of Advanced Robotics and Computer Vision for Shelf Analytics in a Retail Store” (2017, 9 citations), tackles a pressing challenge in large-scale retail: maintaining accurate, real-time inventory on shelves. Trivedi proposed an integrated framework where autonomous robots navigate store aisles, using computer vision to detect and track Stock Keeping Units (SKUs), identify gaps, and flag replenishment needs. This approach moves beyond manual audits toward a scalable, data-driven solution for shelf analytics. By combining robotic mobility with vision-based product recognition, his work addresses the operational friction of out-of-stocks and overstocks—issues that directly impact revenue and customer satisfaction. Trivedi’s contributions are particularly notable for bridging academic computer vision research with practical retail deployment, offering a blueprint for the next generation of autonomous store management. His research continues to influence the growing field of robotic retail analytics, where efficiency, accuracy, and real-time responsiveness are paramount.
Research Focus
Key Achievements
Top Papers
- 1