Papers
9
Total Citations
1,513
H-Index
6
About
Krishna V. Shenoy is a pioneering figure in neural engineering and brain-computer interfaces (BCIs), whose work has fundamentally advanced the restoration of communication and movement for people with paralysis. His research focuses on developing high-performance neural prosthetics by combining insights from motor neuroscience with sophisticated control algorithms. Shenoy’s landmark 2006 paper, “A high-performance brain–computer interface” (707 citations), and his 2012 study on control algorithm design (586 citations) established new benchmarks for cursor and robotic arm control speed and accuracy. He has also led critical translational work, including a 2015 study (124 citations) that assessed BMI design from the perspective of people with paralysis, ensuring that technology development aligns with real-world user needs. More recently, Shenoy has pioneered the use of recurrent neural networks for bimanual movement control (2024) and deep learning for neuroprosthetic control (2023), pushing the field toward more natural, multi-effector capabilities. His achievements include directing the Neural Prosthetics Translational Laboratory at Stanford and receiving the NIH Director’s Pioneer Award. With over 1,500 citations across his most influential works, Shenoy’s research continues to shape the future of clinically viable, high-performance neural interfaces.
Research Focus
Key Achievements
Top Papers
- 1A high-performance brain–computer interface707 citations · 2006
- 2A high-performance neural prosthesis enabled by control algorithm design586 citations · 2012
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- 4Brain control of bimanual movement enabled by recurrent neural networks44 citations · 2024
- 5A Nonhuman Primate Brain–Computer Typing Interface26 citations · 2016
- 6Translating deep learning to neuroprosthetic control14 citations · 2023
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