Dr. Preeya Khanna

Assistant Professor

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Biography

Preeya Khanna received her B.S.E. in Bioengineering and Mathematics from the University of Pennsylvania in 2012 and a Ph.D. from the Joint Graduate Group in Bioengineering at UC Berkeley and UCSF in 2017. She completed her postdoctoral training in the Department of Neurology at UCSF. Her research combines sensorimotor systems neuroscience and network modeling with neurotechnology development to uncover principles of how distributed brain networks coordinate the control of skillful and dexterous movements. These principles are leveraged to design neurophysiologically-grounded brain-machine interface therapies including neurofeedback, myoelectric feedback paradigms, and neuromodulation approaches aimed at restoring movement control in patients with damaged sensorimotor systems.

Research Interests

Human-Computer Interaction Sensorimotor Learning Neural Engineering Brain-Machine Interfaces Rehabilitation Engineering

Requirements for University of California, Berkeley

Doctorate Program
Requirements
GPA Requirement
Required:3
GRE Subject
Overall Score
Required:500
Overall
Required:500
TOEFL
Total
Required:90
IELTS
Overall
Required:7
Prerequisites
Bachelor's degree or recognized equivalent Preparation comparable to undergraduate major at Berkeley in Mathematics or Applied Mathematics 2 full years lower-division work (Calculus, Linear Algebra, Differential Equations, Multivariable Calculus) 8 one-semester upper-division courses (Real Analysis, Complex Analysis, Abstract Algebra, Linear Algebra)
Application Checklist
  • Graduate Application
  • Statement of Purpose
  • Personal History Statement
  • Three Letters of Recommendation
  • Unofficial Transcripts
  • C.V./Resume
  • Course and Textbook List
Specialization Notes

The Mathematics Subject GRE is required for the Fall 2026 admissions cycle. General GRE is optional.