Dishant Patel

University of North Carolina at Charlotte

Papers

Total Citations

H-Index

About

Dishant Patel is a researcher whose work lies at the critical intersection of embedded systems and computer vision, with a particular focus on enabling real-time visual intelligence on resource-constrained devices. His most cited paper, "A Hardware/Software Co-Design Approach for Real-Time Object Detection and Tracking on Embedded Devices" (2018, 7 citations), addresses a fundamental challenge in the field: how to deploy computationally intensive vision algorithms—such as object detection and tracking—on embedded platforms without sacrificing performance. Patel’s key contribution is a co-design methodology that carefully partitions tasks between hardware accelerators and software processing, optimizing for both speed and energy efficiency. This approach is vital for applications ranging from video surveillance and robotics to industrial manufacturing, where real-time visual analysis is essential. By bridging the gap between algorithm design and hardware constraints, Patel’s work provides a practical blueprint for building smarter, more responsive embedded vision systems. His research continues to influence engineers and academics seeking to push the boundaries of what is possible on small, low-power devices, making him a notable voice in the evolution of embedded artificial intelligence.