Saeideh Davoudi (M. Eng.) (elle/she)

Saeideh’s research interests primarily lie in the application of AI in neuroscience. She earned her Bachelor's degree in Electrical Engineering and, driven by her strong interest in medical science and her technical background, pursued a Master’s degree in Biomedical Engineering. Her Master’s thesis, titled “Decoding of Different States of Visual Attention in EEG Using Cross-Frequency Approaches”, laid the foundation for her future research. During this period, she conducted multiple studies on topics such as visual attention, cross-frequency coupling, working memory, and the automatic detection of brain abnormalities. These investigations resulted in several publications in international journals.

In September 2020, Saeideh began her PhD in Neuroscience at the University of Montreal under the supervision of Professor Sarah Lippé. Her doctoral research focuses on identifying EEG markers that best reflect the developmental trajectories of the brain in healthy infants under three years of age. Her recent study has brought major advances in measuring infants' brain maturation with high precision and using only a few minutes of EEG, enabling early and accurate screening for developmental disorders

Conference Presentations:
Saeideh has presented her work at the Organization for Human Brain Mapping (OHBM) with the following posters: