Dr Demi Gao, Senior Research Scientist
Dr Demi X. Gao is a Senior Research Scientist at the Bionics Institute and a Passe and Williams Foundation Mid-Career Fellow.
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 is currently leading research on the digital twin platform to revolutionise cochlear implant. 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.
LinkedIn: https://www.linkedin.com/in/demi-gao-a2333067/
ORCID: 0000-0002-7059-5594
Google Scholar: Dr Demi Xiao Gao
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. 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, Vol.19, e0257568, 2021.
3. O. W. Lee, D. X. Gao, T. Peng, J. Wunderlich, D. Mao, G. Balasubramanian and C. M. McKay. “Measuring Speech Discrimination Ability in Sleeping Infants Using fNIRS—A Proof of Principle”, Trends in Hearing, 29, p.23312165241311721.
4. 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.
5. X. Gao and P. A. Robinson “Importance of self-connections for brain connectivity and spectral connectomics”, Biological Cybernetics, Vol. 114, 643–651, 2020.
