Papers
6
Total Citations
112
H-Index
5
About
Dongjoo Shin is a leading researcher in ultra-low-power artificial intelligence hardware, specializing in energy-efficient processors for autonomous mobile robots and micro-robots. His seminal work on the 2.1 TFLOPS/W mobile deep reinforcement learning accelerator, featuring a transposable processing element array and experience compression, has garnered 59 citations and represents a breakthrough in enabling real-time, intelligent decision-making on resource-constrained platforms. Shin's pioneering 0.55V, 1.1mW AI processor with on-chip PVT compensation, published in 2016 and 2017, demonstrated that sophisticated perception and cognition functions could be realized within the severe power budgets of micro-robots, achieving 25 and 14 citations respectively. He also contributed to the BRAIN low-power deep search engine for autonomous robots, further advancing efficient on-device intelligence. Beyond silicon, Shin has explored flexible wearable sensors using fiber Bragg gratings for motion monitoring and biomedical robotics force sensing. His work directly addresses the critical challenge of implementing heavy computational intelligence without compromising battery life, making him a key figure in the future of autonomous systems and edge AI.
Research Focus
Key Achievements
Top Papers
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- 5BRAIN: A Low-Power Deep Search Engine for Autonomous Robots5 citations · 2017
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