Sachin Patkar

Papers

Total Citations

H-Index

About

Sachin Patkar is a researcher whose work bridges the domains of computer vision and high-performance computing, with a particular focus on real-time stereo vision systems. His most cited paper, "Accelerated Stereo Vision Using Nvidia Jetson and Intel AVX" (2021), demonstrates his expertise in leveraging heterogeneous computing architectures—combining embedded GPU platforms like the Nvidia Jetson with CPU vectorization via Intel AVX—to achieve significant speedups in depth perception tasks. This contribution addresses a critical bottleneck in autonomous systems and robotics, where rapid, accurate 3D scene understanding is essential. While his citation count is still growing, Patkar’s work is notable for its practical emphasis on deployment-ready acceleration techniques, offering a template for optimizing stereo vision algorithms on resource-constrained hardware. His research sits at the intersection of embedded systems, parallel computing, and computer vision, making it particularly relevant for engineers and researchers developing real-time perception pipelines for drones, autonomous vehicles, and mobile robots. Patkar’s approach underscores the importance of co-designing algorithms with hardware capabilities, a key trend in modern edge AI.