Papers
3
Total Citations
13
H-Index
2
About
Zixuan Shen is a rising researcher at the forefront of hardware security and autonomous robotics, specializing in energy-efficient reconfigurable accelerators for edge computing. Their work addresses the critical challenge of balancing performance, power, and area constraints in resource-limited devices. Shen’s most cited paper (9 citations) introduces a reconfigurable cryptographic accelerator for IoT devices, enabling low-cost, high-performance network security for intelligent sensors and mobile robots. This work is foundational for securing the expanding Internet of Things ecosystem. Building on this, Shen has pioneered hardware acceleration for autonomous mobile robots (AMRs), including a live demonstration of an EKF-SLAM accelerator SoC that integrates multi-sensor fusion (LiDAR and wheel encoders) on a ZYNQ-7000 FPGA. Most notably, Shen developed a low-hardware-overhead, end-to-end CNN-based feature extraction accelerator for visual SLAM, tackling the computational demands of SuperPoint neural networks. This innovation bridges the gap between deep learning accuracy and real-time deployment on edge devices. With a clear trajectory from cryptographic security to autonomous navigation, Shen’s work is shaping the future of intelligent, secure, and energy-efficient robotic systems.
Research Focus
Key Achievements
Top Papers
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