Yijing Watkins

Pacific Northwest National Laboratory

Papers

1

Total Citations

18

H-Index

1

About

Yijing Watkins is a leading researcher at the intersection of neuromorphic computing and energy-efficient artificial intelligence. Her work focuses on developing and benchmarking biologically inspired algorithms for next-generation hardware, with particular emphasis on sparse coding and the Locally Competitive Algorithm (LCA). In her highly cited 2023 paper, "Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor," she demonstrated how LCA can achieve remarkable power efficiency on Intel’s Loihi 2 processor, building on foundational work with its predecessor. This contribution is pivotal for advancing low-power, real-time AI systems, offering a path toward scalable neuromorphic solutions that mimic neural processing. With 18 citations and growing impact, Watkins’ research is shaping the future of hardware-software co-design for intelligent edge devices. Her achievements highlight a commitment to bridging theoretical neuroscience with practical engineering, making her a key figure in the push for sustainable, high-performance computing.

Research Focus

Key Achievements

1
H-Index
1
Papers
18
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor
18 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Pacific Northwest National Laboratory

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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