Dr Reza Shoorangiz

BSc, MSc, PhD

Project Researcher

New Zealand Brain Research Institute, 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.

2018

Download Stress-evoking emotional stimuli exaggerate deficits in motor function in Parkinson’s disease.
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, 66-76. 10.1016/j.neuropsychologia.2018.03.006
Download Predicting microsleep states using EEG inter-channel relationships.
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, 2260 - 2269. 10.1109/TNSRE.2018.2878587

Abstracts and Short papers

2019

Download Deep learning with convolutional neural network for detecting microsleep states from EEG: A comparison between the oversampling technique and cost-based learning.
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, 4152-4155.
Download Detection and prediction of microsleeps from EEG using spatio-temporal patterns.
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, 522-525.

2018

Download Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG.
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, 3036-3039.

2017

Download Bayesian multi-subject factor analysis to predict microsleeps from EEG power spectral features.
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, 4183-4186.

2016

Download Prediction of microsleeps from EEG: preliminary results.
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, 4650-4653.