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Dr Demi Gao, Senior Research Scientist

Dr Demi Gao is a Senior Research Scientist at the Bionics Institute and Honorary Research Fellow in the Medical Bionics Department, University of Melbourne.

Demi’s research program spans the fields of neural engineering, biomedical engineering, brain imaging and machine learning to understanding human hearing system, including developing techniques for hearing loss diagnosis and optimising the performance of next-generation cochlear implants.

Demi possesses a broad multidisciplinary skill set with a diverse research background encompassing information technology, neural engineering, and bio-signal processing. Since completing her PhD in December 2016, Demi has been awarded over $ 1 Million research fundings as a solo investigator. Demi was awarded a McKenzie Early-Career Fellowship from the University of Melbourne (2019 – 2022), a MRFF MTPConnect Researcher Exchange and Development within Industry (REDI) Fellowship (2022 – 2023) and a Passe and Williams Foundation Mid-Career Fellowship (2024 – 2026).

At Bionics Institute, Demi joined the Translation Hearing Research team led by Professor Colette McKay. Demi is currently leading research on enabling improved cochlear implant programming for infants. In addition, she is also part of the EarGenie® team to develop diagnostic tools for accurate and comprehensive assessment of babys’ hearing based on functional near-infrared spectroscopy (fNIRS) measurement.

 

E: [email protected]

LinkedIn: https://www.linkedin.com/in/demi-gao-a2333067/

ORCID: 0000-0002-7059-5594

Google Scholar: Dr Demi Xiao Gao

Research projects

Improved cochlear implant programming for infants

EarGenie hearing test for babies

Selected publications

  1. E. R. Zoneff, D. X. Gao, D. R. Nisbet, D. B. Grayden, and G. M. Clark. “Restoration of the senses and human communication: Sustainable Development Goals 3 and 9.” International Journal of Speech-Language Pathology (2022): 1-6.
  2.  P. A. Robinson, X. Gao, Y. Han “Relationships between lognormal distributions of neural properties, activity, criticality, and connectivity”, Biological Cybernetics 115, 121-130, 2021.
  3. X. Gao, D. B. Grayden and M. D. McDonnell “Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants”, PloS ONE 16, e0257568, 2021.
  4. X. Gao and P. A. Robinson “Importance of self-connections for brain connectivity and spectral connectomics”, Biological Cybernetics, Vol. 114, 643–651, 2020.
  5. X. Gao, D. B. Grayden and M. D. McDonnell “Modeling electrode place discrimination in cochlear implant stimulation,” IEEE Transactions on Biomedical Engineering, Vol. 64, 2219-2229, 2016.

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