Hailong Jiao
Papers
1
Total Citations
1
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1
About
Hailong Jiao is a leading researcher in energy-efficient hardware acceleration for neural networks, with a particular focus on point-cloud processing and 3D deep learning. His work addresses the critical challenge of deploying complex neural networks in resource-constrained environments, from autonomous vehicles to edge devices. Jiao’s most notable contribution is the Nebula accelerator, a 28nm 109.8TOPS/W 3D PNN processor that introduces adaptive partition, multi-skipping, and block-wise aggregation techniques. This design achieves exceptional energy efficiency while maintaining high throughput for point-cloud analysis, outperforming prior accelerators by a significant margin. His research has garnered attention for pushing the boundaries of hardware-software co-design, with his top-cited paper already accumulating citations in its first year. Jiao’s innovations enable real-time, low-power 3D perception for autonomous driving, robotics, and virtual reality applications. By bridging the gap between algorithmic advances and practical hardware implementation, he is shaping the future of efficient AI computing. His work continues to inspire new directions in specialized accelerator design for emerging neural network architectures.
Research Focus
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Top Papers
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