Nishal Shah

WEBSITE(S)| Rice Brain Computer Interface Lab

Nishal Shah is an Assistant Professor in the Electrical and Computer Engineering department at Rice, a core member of the Rice Neuroengineering Initiative, and a McNair Medical Scholar.

He completed his Bachelor's and Master's in Electrical Engineering at the Indian Institute of Technology, Delhi in 2013. Subsequently, he finished his PhD in Electrical Engineering from Stanford University’s Artificial Retina Group in 2020, where his research focused on developing computational approaches to restore vision by electrically stimulating retinal ganglion cells. He then worked as a Milton Safenowitz postdoctoral researcher at Stanford's Neural Prosthetics Translational Lab and as a member of the BrainGate2 consortium until 2024, where his research focussed on developing communication interfaces by decoding high degrees-of-freedom finger movements from the motor cortical recordings of participants with paralysis who are surgically implanted with microelectrode arrays.

His lab aims to build a computational toolbox for reading out and writing in information to neural circuits in real-time and at cellular resolution.

His lab seeks to answer the following issues:

  1. How are flexible, high-degrees of freedom movements such as finger movements, limb movements, and speech represented in the brain?
  2. Can we use intracortical microelectrode array recordings in human participants with paralysis to enable full-body movement in virtual reality? 
  3. How do we reproduce rich spatio-temporal neural activity patterns using electrical stimulation?
  4. How do we use existing experimental data to develop the next-generation of low-power, large-scale and high-density implantable BCIs?

His lab will make progress towards these questions by collaborating with hardware groups, basic neuroscientists, and clinicians, both at Rice University and the Texas Medical Center.

 

Research Areas

intracortical brain computer Interfaces (BCIs), electrical stimulation, closed loop BCIs, computational neuroscience, neural signal processing

Education

2020, PhD in Electrical Engineering, Stanford University

2013, B.S./M.S. in Electrical Engineering, Indian Institute of Technology, Delhi

Honors & Awards

Milton Safenowitz Postdoctoral Fellowship (2020) by ALS Association

Numerical Technical Founders’ Fellowship (2014)

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