I use machine learning in two specific fields of research: neuroengineering and adaptive optics. Our CDA website details other areas of our research.
Qualifications & Memberships
Research interests include:
-Embedded Systems - Control
-Digital Signal Processing - Imaging and Control, Applications
-Machine learning for prediction and classification
-Heterogeneous computer systems architecture
-Systolic computer architectures
-Digital signal and digital image processing
- Baseer Buriro A., Shoorangiz R., Weddell SJ. and Jones RD. (2018) Predicting microsleep states using EEG inter-channel relationships. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26(12): 2260-2269. http://dx.doi.org/10.1109/TNSRE.2018.2878587.
- Buriro AB., Shoorangiz R., Weddell SJ. and Jones RD. (2018) Ensemble learning based on overlapping clusters of subjects to predict microsleep states from EEG.. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2018-July: 3036-3039. http://dx.doi.org/10.1109/EMBC.2018.8512962.
- Peimankar A., Weddell SJ., Jalal T. and Lapthorn A. (2018) Multi-objective ensemble forecasting with an application to power transformers. Applied Soft Computing 68: 233-248. http://dx.doi.org/10.1016/j.asoc.2018.03.042.
- Weddell SJ. and Bones P. (2018) Wavefront prediction with reservoir computing for minimizing the effects of angular anisoplanatism. Journal of Applied Optics.
- Knopp S., Bones P., Weddell SJ. and Jones R. (2017) A software framework for real-time multi-modal detection of microsleeps. Australasian Physical and Engineering Sciences in Medicine 40(3): 739-749. http://dx.doi.org/10.1007/s13246-017-0559-x.
Refer to our CDA website for details about our group: https://researchprofile.canterbury.ac.nz/Group.aspx?groupid=45