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
- Engler B., Le Louarn M., Verinaud C., Weddell S. and Clare R. (2022) A flip-flop modulation method used with a pyramid wavefront sensor to correct piston segmentation on ELTs. Journal of Astronomical Telescopes, Instruments, and Systems JATIS21114SSR.
- Buriro AB., Ahmed B., Baloch G., Ahmed J., Shoorangiz R., Weddell S. and Jones R. (2021) Classification of alcoholic EEG signals using wavelet scattering transform-based features. Computers in Biology and Medicine 139 104969 http://dx.doi.org/10.1016/j.compbiomed.2021.104969`.
- Buriro AB., Ahmed B., Baloch G., Ahmed J., Shoorangiz R., Weddell SJ. and Jones RD. (2021) Classification of alcoholic EEG signals using wavelet scattering transform-based features. Computers in Biology and Medicine 139 http://dx.doi.org/10.1016/j.compbiomed.2021.104969.
- Pal S., Clare R., Lambert A. and Weddell S. (2021) Multiscale optimization of the geometric wavefront sensor. Applied Optics 60(25): 7536-7544. http://dx.doi.org/10.1364/AO.423536.
- Weddell S., Ayyagari S. and Jones R. (2021) Detection of microsleep states from the EEG: A comparison of feature reduction methods. Medical and Biological Engineering and Computing MBEC-D-20-00240R2.
Refer to our CDA website for details about our group: https://researchprofile.canterbury.ac.nz/Group.aspx?groupid=45