Muya Chang
Papers
4
Total Citations
66
H-Index
3
About
Muya Chang is pioneering the intersection of energy-efficient hardware design and autonomous swarm robotics, with a focus on creating ultra-low-power computing platforms for miniature robotic systems. Their research centers on hybrid-digital-mixed-signal architectures that dramatically reduce energy consumption while maintaining high computational throughput, enabling real-time artificial swarm intelligence at the edge. Chang’s most influential work, a 65nm computing platform achieving 1.1-to-9.1 TOPS/W, has garnered 31 citations for demonstrating how biologically-inspired swarm algorithms can be accelerated in silicon. This platform, along with its 18-citation follow-up, established new benchmarks for energy-proportional computing in robotics. More recently, Chang has advanced the field with a 40nm VLIW edge accelerator integrating 5MB of embedded RRAM (0.256 pJ/bit) and a dedicated localization solver for bristle robot surveillance—a 15-citation breakthrough that balances neural network inference with state-space equation solving in a compact, low-power form factor. By addressing the stringent energy and size constraints of tiny autonomous robots, Chang’s work directly enables practical applications in surveillance, environmental monitoring, and distributed sensing, positioning them as a leading architect of next-generation edge intelligence for robotic swarms.
Research Focus
Key Achievements
Top Papers
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