Calvin Eiber

Dr Calvin Eiber is a biomedical researcher and computational neuroscientist with a broad background in neural interface research. His primary background is at the interface between biomedical engineering and visual neuroscience, with specific training and expertise in medical electronics, computational modelling of living tissue, and the physiology of vision. He has a broad body of work which includes the development of new ways to stimulate and record neural activity across spatial and temporal scales, using techniques such as current steering and electrical impedance tomography, as well as more fundamental work on understanding how visual signals are represented and processed in the sub-cortical visual system. Calvin completed his Ph.D. in 2015 at UNSW as part of the Australian Bionic Eye Project, followed by a postdoctoral research position at the Save Sight Institute at the University of Sydney in conjunction with the ARC Centre of Excellence for Integrative Brain Function. He is currently a research fellow in the Keast-Osborne lab in the Department of Anatomy and Neuroscience, working on computational modelling of neural interfaces for the autonomic nervous system as part of the NIH "Stimulating Peripheral Activity to Relieve Condition" (SPARC) project, and is also a co-chair of the IEEE standards committee "Reporting Standards for In Vivo Neural Interface" (P2794).

  • Contact Details
    Department:Anatomy and Neuroscience
  • Current Research Focus

    Computational modelling of peripheral neural interfaces

    Field of ResearchDescription
    110901Autonomic Nervous System
    110906Sensory Systems
  • Key Skills
    • Neuroscience
    • Computational Modelling
    • MATLAB and Neuron anatomically-detailed models of neural cells, circuits, and systems
    • Computational Geometry (for, e.g., automated microscopy image processing)
  • Looking to collaborate?

    I’m looking to collaborate with electrophysiologists and other neural recording experts who have found themselves with hard-to-explain results, in order to better understand the roles of systems and feedback in determining the body’s neural codes.