Vinayak Gokhale
Papers
1
Total Citations
43
H-Index
1
About
Vinayak Gokhale is a leading researcher in efficient deep learning and embedded systems, with a focus on deploying complex neural networks on resource-constrained hardware. His most-cited work, "An efficient implementation of deep convolutional neural networks on a mobile coprocessor" (2014, 43 citations), pioneered the hardware-accelerated, real-time execution of DCNNs on mobile platforms. This contribution addressed the critical challenge of managing the hundreds of intermediate results generated by deep networks, enabling practical applications in mobile and edge computing. Gokhale’s research has significantly advanced the intersection of computer architecture and machine learning, demonstrating how coprocessors can bridge the gap between computational demands and mobile device limitations. His work has influenced subsequent developments in low-power AI inference, earning recognition for its impact on both academic research and industrial applications. By optimizing neural network performance on mobile coprocessors, Gokhale has helped democratize deep learning, making it accessible for real-world, on-device tasks such as image recognition and augmented reality.
Research Focus
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Top Papers
- 1