Papers

2

Total Citations

21

H-Index

2

About

Ruixiao Liu is pioneering the future of human–machine interaction and flexible electronics through innovative integration of deep learning and advanced materials. Their research focuses on two key frontiers: noise-tolerant wearable sensor systems and novel interface engineering for two-dimensional semiconductors. Liu’s most cited work, “A noise-tolerant human–machine interface based on deep learning-enhanced wearable sensors” (2025, 15 citations), introduces a robust framework that combines machine learning with flexible sensors to create reliable, real-time control interfaces—a critical step toward practical prosthetics and smart wearables. In parallel, Liu’s study on “Enhanced Electrical Interfaces in Flexible 2D Material Transistors via Liquid Metal and Ionic Liquid Injection” (2025, 6 citations) proposes a groundbreaking solid–liquid hybrid paradigm for field-effect transistors, addressing long-standing contact engineering challenges at semiconductor–electrode and semiconductor–dielectric interfaces. This work promises to unlock the full potential of delicate 2D materials in bendable, high-performance electronics. By merging computational intelligence with materials innovation, Liu is shaping a new generation of adaptive, noise-resilient devices that bridge the gap between soft biological systems and rigid electronics.

Research Focus

Key Achievements

2
H-Index
2
Papers
21
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A noise-tolerant human–machine interface based on deep learning-enhanced wearable sensors
15 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 38
🏛 Institutions: University of California San Diego, University of Michigan–Ann Arbor

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
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