Associate Professor Charles Peter Unsworth

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Associate Professor


  • Associate Professor

Associate Professor Charles Unsworth is Director of the Neural Engineering Group, which he established in 2002. His group specialises in Neural Chip in vitro models, Advanced Nonlinear Signal & Image Processing, Artifical Neural Networks & Machine Learning and Computational Neuroscience in the Department of Engineering Science, The University of Auckland, New Zealand.

He holds a BSc Hons in Mathematical Physics from the University of Liverpool, an MSc in Astronomical Technology from Edinburgh University’s Royal Observatory, and a PhD in Millimeter-Wave Physics at the University of St Andrews. He was a Higher Scientific Officer of the Defence Evaluation Research Agency (DERA) at the Ministry of Defence, UK, in the area of radar hardware. He completed a 3 year Postdoctoral Fellow at the University of Edinburgh in Radar Signal Processing and a 2 year Postdoctoral Mobility Fellow at Edinburgh University collaborating with the Royal Hospital of Sick Children, Edinburgh in Biomedical Signal Processing. He joined the Department of Engineering Science in 2002.


PhD Millimeter-Wave Physics, University of St Andrews
MSc Astronomical Technology, Royal Observatory, University of Edinburgh
BSc(Hons) in Mathematical Physics, University of St Andrews

PGCert Academic Practice

External Service

Editorial Board Member, Technology, World Scientific Publishing: (2017-present)

IEEE EMBS Technical Committee Member on Neural Engineering (2018-present)

Professional Memberships


Research | Current

Neural Engineering Areas of Research

We have 3 broad areas of research. If you interested in these or related areas. Please feel free to contact me by email.

In vitro Neural Chip Platforms: Our research is focussed on understanding the basic science of communication in the brain by combining both the fields of Cell Patterning  and ‘Multi-Electrode-Arrays’(MEAs) which are concerned with arrangement, control and stimulation/recording of cells on silicon chip. By applying novel laser cell steering and laser ablative microsurgery to highly organise and prune cell networks to a high fidelity. This has enabled our group to create a transformative chip technology allowing for the construction of precise large-scale regular grid networks of human neurons or astrocytes on chip, which are individually addressable, electrically and photonically, at the cellular level, such that communication can be mapped accurately from the single-cell level to large network scales. This platform technology will allow for the mapping of signal propagation in real neural networks from the single cell level through to large network scales. The novelty is that we organise the neural cells into regular grid arrays so that communication can be more effectively and repeatably studied.  We then apply nonlinear signal processing strategies such as Artificial Neural Networks and Machine Learning techniques, Wavelets and Chaos theory to extract/analyse/predict from the multi-channel data obtained from the chip work. We then build mathematical and computational models from the multi-channel data on chip. The technology would help provide insights into debilitating human neuropathologies such as epilepsy, stroke and hypoxic ischemia and provide a silicon chip platform technology to facilitate broader neuroscientific discovery. This work has been funded by the Royal Society of New Zealand's Marsden Fund.

Detecting Biomarkers in the EEG with Artificial Neural Networks & Machine Learning: 

The second research area, is in the development of automated machine learning algorithms to detect biomarkers in the EEG in order to predict hypoxic ischemia (HI) in new-born infants and to correlate them with brain injury. We have developed Wavelet-Fuzzy System classifiers, that can accurately classify and quantify HI sharp and HI spike wave transients and correlate this to brain damage from histology samples. Hence, we have identified the Sharp wave as the first EEG biomarker of HI injury. Such automated detection for hypoxia ischemia would provide a breakthrough in real-time detection and would allow for treatment to be administered. Currently, we are developing algorithms to apply this to human pretern infants to identify biomarkers of hypoxia ischemia. This work has been funded by the Health Research Council and the Auckland Medical Research Foundation.

Molecular Predictors for Ultra-sensitive Biosensors using Artificial Neural Networks & Machine Learning: 

The third research area is involved with the development of Artificial Neural Networks as the classification backend of ultrasensitive e-nose biosensors. We have demonstrated how Artificial Neural Networks (ANNs) can be successfully incorporated as the signal processing back end of the biosensor to drastically reduce the number of receptors to 3-5 while still retaining a very high performance of odorant detection to that of a full complement of receptors. Recently, we have embarked upon new related research to predict hormones in complex liquid environments from ultra-sensitive apatamer biosensors. This work has been funded by the Ministry of Buisness, Innovation & Employment (MBIE) and Royal Society of New Zealand's Marsden Fund.

Teaching | Current


  • ENGSCI 313 - Mathematical Modelling 3ECE
  • ENGSCI 314 - Mathematical Modelling 3ES
  • ENGSCI 311 - Mathematical Modelling 3
  • ENGSCI 309 - Image & Digital Signal Processing
  • ENGSCI 712 - Computational Algorithms in Signal Processing

Postgraduate supervision

Graduated Postgraduate Students (7 PhD, 2 ME)

PhD     Brad Raos, (UoA Doctoral Scholarship) - Primary supervisor (Graduated October 2018 – Deans honors List 2018, Nominated by Faculty for VC Best Doctoral Thesis Award)

PhD     Hamid Abbasi,  - Primary supervisor (Graduated October 2018)

PhD     Zarrar Javaid - Primary supervisor. (Graduated October 2016)

PhD     Sepideh Rastin - Primary supervisor . (Graduated May 2016)

PhD     Alireza Nejati – Primary Supervisor. (Graduated October 2015)

PhD     Jonathan Leaver - Primary supervisor. (Graduated May 2007)

PhD      Branislav Jovic - Primary supervisor. (Graduated May 2008 – Awarded Best UoA Doctoral Thesis Award)

ME       Johanna Im - Primary supervisor. (Graduated May 2007)

ME       Luqman Bachtiar - Primary supervisor. (Graduated July 2012)


Current Postgraduate Students (7 PhD, 1 ME)

PhD     Yi Wang - Primary supervisor. (China Scholarship)

PhD     Mohsen Maddah, (start April 2016) – Second supervisor. (Royal Scoeciety of New Zealand Funded)

PhD     Si Li,(start April 2016) – Primary supervisor. (Awarded the ‘AUEA Braithwaite-Thompson Graduate Research Award ’, July 2019)

PhD     Saheli Battacharya, (start Dec 2016) – Primary supervisor. (University of Auckland Doctoral Scholar)

PhD     SeyedHamid Mashadi Moghaddam, (started 2015, part-time) - 2nd Supervisor.

PhD     Angela Prieto Rodriguez, - 2nd Supervisor, (completed 2019)

ME       Ben Warren, - Primary Supervisor (started June 2018)


(2017-present) Associate Investigator of the MacDiarmid Institute, Centre of Research Excellence 

(2017-present) Honorary Research Associate of VUW

2018 Visiting Professorship at Tampere University, Finland

2009 Awarded a UK, Engineering & Physical Sciences Research Council Visiting Fellowship

2006 Awarded the University of Auckland's 'Certificate of University Learning & Teaching'


University Service

(Jan 2018 - present) Elected Faculty Representative Subprofessorial Senate Member

 (Jan 2014-present) Faculty Representative on the University Human Participants Ethics Committee (HPEC)

Areas of expertise

  • Neural Engineering
  • Advanced Signal & Image Processing
  • Mathematical & Computational Neuroscience

Committees/Professional groups/Services


Professional affiliations

  • Professional Member of the Institute of Electrical and Electronics Engineers (MIEEE)
  • Professional Member of the Institution of Engineering and Technology (MIET)
  • Professional Member of the Royal Society of New Zealand (MRSNZ)
  • Professional Member of the Engineering in Medical & Biology Society (MEMBS)
  • Member of the New Zealand Mathematical Society (NZMS)
  • Member of the Auckland Neuroscience Network (ANN)
  • Member of the Tertiary Education Union (TEU)

Selected publications and creative works (Research Outputs)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.
  • Abbasi, H., & Unsworth, C. P. (2020). Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalogram. Neural Regeneration Research, 15 (2), 222-231. 10.4103/1673-5374.265542
    Other University of Auckland co-authors: Hamid Abbasi
  • Abbasi, H., Bennet, L., Gunn, A. J., & Unsworth, C. P. (2019). Latent phase detection of hypoxic-ischemic spike transients in the EEG of preterm fetal sheep using reverse biorthogonal wavelets& fuzzy classifier. International Journal of Neural Systems, 29 (10)10.1142/S0129065719500138
    Other University of Auckland co-authors: Hamid Abbasi, Laura Bennet, Alistair Gunn
  • Li, S., Simpson, M. C., Graham, E. S., & Unsworth, C. P. (2019). Large 10  ×  10 single cell grid networks of human hNT astrocytes on raised parylene-C/SiO2 substrates. Journal of neural engineering, 16 (6)10.1088/1741-2552/ab39cc
    Other University of Auckland co-authors: Scott Graham
  • Li, S., Simpson, M. C., Graham, E. S., & Unsworth, C. P. (2019). Single Cell Grid Networks of Human Astrocytes On Chip. Proceedings 2019 9TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 502-505. San Francisco, CA: IEEE. 10.1109/NER.2019.8717032
    Other University of Auckland co-authors: Scott Graham
  • Li, S., Simpson, M. C., Graham, E. S., & Unsworth, C. P. (2019). Activating a 2x2 Network of hNT Astrocytes with UV Laser Stimulation. Proceedings 2019 9TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 506-509. San Francisco, CA: IEEE. 10.1109/NER.2019.8717185
    Other University of Auckland co-authors: Scott Graham
  • Raos, B. J., Simpson, M. C., Doyle, C. S., Graham, E. S., & Unsworth, C. P. (2019). Evaluation of parylene derivatives for use as biomaterials for human astrocyte cell patterning. PloS one, 14 (6)10.1371/journal.pone.0218850
    Other University of Auckland co-authors: Brad Raos, Scott Graham
  • Maddah, M., Unsworth, C. P., & Plank, N. O. (2019). Selective growth of ZnO nanowires with varied aspect ratios on an individual substrate. MATERIALS RESEARCH EXPRESS, 6 (1)10.1088/2053-1591/aae6a2
  • Bennet, L., Galinsky, R., Draghi, V., Lear, C. A., Davidson, J. O., Unsworth, C. P., & Gunn, A. J. (2018). Time and sex dependent effects of magnesium sulphate on post-asphyxial seizures in preterm fetal sheep. The Journal of physiology, 596 (23), 6079-6092. 10.1113/jp275627
    Other University of Auckland co-authors: Alistair Gunn, Laura Bennet, Christopher Lear

Contact details

Primary office location

Level 3, Room 335
New Zealand