Dr Reza Shoorangiz
BSc, MSc, PhD
Research Fellow
New Zealand Brain Research Institute, Christchurch
Deputy Director
Christchurch Neurotechnology Research Programme, Christchurch
Adjunct Fellow
Department of Electrical and Computer Engineering, University of Canterbury, Christchurch
Adjunct Fellow
Department of Medicine, University of Otago, Christchurch
I received my Bachelor's degree in electrical engineering from Shiraz University, Shiraz, Iran, in 2010. In 2013, I received a Master's degree in control and automation engineering from Universiti Putra Malaysia, Selangor, Malaysia. My thesis was entitled: "Adaptive Complex Neuro-Fuzzy Inference System for Nonlinear Modeling and Time Series Prediction".
I received my PhD degree from Electrical & Computer Engineering at University of Canterbury on 'Bayesian approaches to detection and prediction of lapses of responsiveness'. My research is concentrated on detection and prediction of lapses of responsiveness, using a Bayesian approach. The latter is a probabilistic method which can represent human brain interactions in term of probabilities and handle uncertainties.
Publications
Provided on request for non-commercial personal use by researchers.
2021
Buriro, A. B., Ahmed, B., Baloch, G., Ahmed, J., Shoorangiz, R., Weddell, S. J., Jones, R. D. (2021). Classification of alcoholic EEG signals using wavelet scattering transform-based features. Computers in Biology and Medicine,
139 (104969), .
10.1016/j.compbiomed.2021.104969
Horne, K., MacAskill, M. R., Myall, D. J., Livingston, L., Grenfell, S., Pascoe, M. J., Young, B., Shoorangiz, R., Melzer, T. R., Pitcher, T. L., Anderson, T. J., Dalrymple‐Alford, J. C. (2021). Neuropsychiatric symptoms are associated with dementia in Parkinson’s disease but not predictive of it. Movement Disorders Clinical Practice,
8, .
10.1002/mdc3.13151
Shoorangiz, R., Weddell, S.J., Jones, R.D. (2021). EEG-Based Machine Learning: Theory and Applications. ,
In N. V. Thakor (Ed.) Handbook of Neuroengineering. Springer, Singapore..
10.1007/978-981-15-2848-4_70-1
2020
MacAskill, M. R., Myall, D. J., Shoorangiz, R., Anderson, T. J., Pitcher, T. L. (2020). Childbirth and delayed Parkinson’s onset: a reproducible non-biological artefact of societal change. Movement Disorders,
35, .
10.1002/mds.28135
Melzer, T.R., Keenan, R.J., Leeper, G.J., Kingston-Smith, S., Felton, S.A., Green, S.K., Henderson, K.J., Palmer, N.J., Shoorangiz, R., Almuqbel, M.M., Myall, D.J. (2020). Test-retest reliability and sample size estimates after MRI scanner relocation. Neuroimage 211, .
10.1016/j.neuroimage.2020.116608
2018
Blakemore, R. L., MacAskill, M. R., Shoorangiz, R., Anderson, T. J. (2018). Stress-evoking emotional stimuli exaggerate deficits in motor function in Parkinson’s disease. Neuropsychologia,
112, .
10.1016/j.neuropsychologia.2018.03.006
Buriro, A. B., Shoorangiz, R., Weddell, S. J., Jones, R. D. (2018). Predicting microsleep states using EEG inter-channel relationships. IEEE Transactions on Neural Systems and Rehabilitation Engineering,
26, .
10.1109/TNSRE.2018.2878587
2013
Shoorangiz, R., Marhaban, M. H. (2013). Complex neuro-fuzzy system for function approximation. International Journal of Applied Electronics in Physics & Robotics, 1(2),
1 (2), .
10.7575/aiac.ijaepr.v.1n.2p.5
Yunusa, Z., Dan-Isa, A., Ali Sai’d, Y., Shoorangiz, R. (2013). Effects of the number of rules on the quality of fuzzy logic control of induction motor. International Journal of Applied Electronics in Physics & Robotics,
1(1), .
10.7575/aiac.ijaepr.v.1n.1p.14
Abstracts and Short papers
2021
Deane, A., Liu, P., Shoorangiz, R., Jing, Y., Ward, R. (2021). In search of lost time: Cognitive and arginine metabolic correlates of temporal dysfunction in the MIA rat model of schizophrenia risk [Preprint]. PsyArXiv.
10.31234/osf.io/w759f
Zaky, M. H., Shoorangiz, R., Poudel, G. R., Yang, L., Jones, R. D. (2021). Investigating the neural signature of microsleeps using EEG. Proceedings of International Conference of IEEE Engineering in Medicine and Biology Society,
43, .
2020
Horne, K.-L., MacAskill, M. R., Myall, D., Livingston, L., Grenfell, S., Pascoe, M. J., Young, B., Shoorangiz, R., Melzer, T. R., Pitcher, T. L., Anderson, T. J., Dalrymple-Alford, J. C. (2020). Neuropsychiatric symptoms are associated with dementia in Parkinson’s disease but not predictive of it. MedRxiv, 2020, 09,
01, .
https://doi.org/10.1101/2020.09.01.20186312
Zaky, M. H., Shoorangiz, R., Poudel, G. R., Yang, L., Jones, R. D. (2020). Neural correlates of attention lapses during continuous tasks. Proceedings of International Conference of IEEE Engineering in Medicine and Biology Society,
42, .
2019
Krishnamoorthy, V., Shoorangiz, R., Weddell, S. J., Beckert, L., Jones, R. D. (2019). Deep learning with convolutional neural network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based learning. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society,
41, .
Shoorangiz, R., Buriro, A. B., Weddell, S. J., Jones, R. D. (2019). Detection and prediction of microsleeps from EEG using spatio-temporal patterns. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society,
41, .
2018
Buriro, A. B., Shoorangiz, R., Weddell, S. J., Jones, R. D. (2018). Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society,
40, .
2017
Shoorangiz, R., Weddell, S. J., Jones, R. D. (2017). Bayesian multi-subject factor analysis to predict microsleeps from EEG power spectral features. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society,
39, .
2016
Shoorangiz, R., Weddell, S., Jones, R.D. (2016). Prediction of microsleeps from EEG: preliminary results. Proceedings of Annual International Conference of IEEE Engineering in Medicine and Biology Society, Orlando,
38, .
_2013.pdf.jpeg)
![Download In search of lost time: Cognitive and arginine metabolic correlates of temporal dysfunction in the MIA rat model of schizophrenia risk [Preprint].](/resources/publications/650/Deane_PsyArXiv_2021.pdf.jpeg)
