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About Hanieh
Dr. Hanieh Bakhshayesh serves as a Senior Lecturer in the School of Electrical Engineering, Computing and Mathematical Sciences within the Faculty of Science and Engineering at Curtin University. She holds a PhD and a B.Eng (Honours) from Flinders University, where her honours thesis focused on synchronization in the brain under the supervision of Kenneth J. Pope. Prior to her current role, she was affiliated with Flinders University's College of Science and Engineering, contributing to research on EEG signal processing and neural connectivity. Her academic career emphasizes advancements in biomedical signal analysis, bridging electrical engineering with neurophysiological applications.
Dr. Bakhshayesh's research specializations include signal processing and biomedical engineering, with a focus on EEG functional connectivity, effective connectivity measures, and emerging neuroimaging techniques. Key publications feature 'Detecting synchrony in EEG: A comparative study of functional connectivity measures' (Computers in Biology and Medicine, 2018), co-authored with Sean P. Fitzgibbon, Azin S. Janani, Tyler S. Grummett, and Kenneth J. Pope; 'Detecting connectivity in EEG: A comparative study of data-driven effective connectivity measures' (Computers in Biology and Medicine, 2019); 'An Investigation of the Nature of Fear within ACL-Injured Subjects When Exposed to Provocative Videos: A Concurrent Qualitative and Quantitative Study' (Sports, 2022), in collaboration with Cameron Little and Darren Beales; and 'Understanding Fear after an Anterior Cruciate Ligament Injury: A Rapid Review' (International Journal of Environmental Research and Public Health, 2023). Her work also encompasses near-infrared spectroscopy (NIRS) applications for brain activity monitoring during memory tasks, aimed at early Alzheimer's disease detection, as well as online condition monitoring of overhead insulators using pattern recognition. At Curtin University, she supervises postgraduate research projects and teaches courses such as electrical circuits. Her contributions have garnered citations exceeding 270, influencing methodologies in EEG analysis and interdisciplinary neurophysiology studies.
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