Geeling Chau

California Institute of Technology

Papers

2

Total Citations

57

H-Index

2

About

Geeling Chau is pioneering the next generation of brain-machine interfaces (BMIs) by harnessing the power of functional ultrasound (fUS) neuroimaging. Her research focuses on developing closed-loop, ultrasonic BMIs that decode motor plans directly from brain activity, offering a transformative solution for individuals with chronic paralysis. Chau’s major contribution lies in demonstrating that fUS—a less invasive, high-resolution imaging technique—can achieve real-time, closed-loop control, overcoming the traditional trade-offs between invasiveness, performance, and spatial coverage found in existing BMIs. Her seminal 2023 paper, "Decoding motor plans using a closed-loop ultrasonic brain–machine interface," has already garnered 51 citations, underscoring its impact on the field. This work, alongside her 2022 study, shows that ultrasonic BMIs can bypass neurological impairments, enabling users to control computers, robots, and other devices through thought alone. Chau’s innovative approach not only advances neuroprosthetics but also opens new avenues for high-performance, scalable neural interfaces, making her a rising leader in translational neuroscience.

Research Focus

Key Achievements

2
H-Index
2
Papers
57
Total Citations
29
Avg Citations/Paper
🏆 Most Cited Paper
Decoding motor plans using a closed-loop ultrasonic brain–machine interface
51 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: California Institute of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago