About Me
I’m currently pursuing my second Master’s degree in Neuroscience at the University of Western Ontario in the Mohsenzadeh Lab, under the supervision of Dr. Yalda Mohsenzadeh and Dr. Emma Duerden.
My current research investigates visual processing in the human brain using simultaneous EEG–fNIRS recordings. By integrating these two complementary neuroimaging modalities, I aim to capture both the temporal and hemodynamic aspects of visual perception, contributing to a more comprehensive understanding of how the brain integrates and represents visual information.
Before joining Western, I completed my M.Sc. in Artificial Intelligence and Robotics at the University of Tehran under the supervision of Dr. Mohammadreza Abolghasemi Dehaqani. My thesis focused on investigating the brain’s automatic change detection ability using a neural signature known as Visual Mismatch Negativity (vMMN).
We explored this Event-Related Potential (ERP) component within the predictive coding framework, aiming to disentangle repetition-related and expectation-related effects contributing to vMMN. To achieve this, I designed a Rapid Serial Visual Presentation (RSVP) paradigm inspired by Summerfield et al. (2008), where we recorded EEG signals while participants viewed complex visual stimuli. This approach allowed us to move beyond traditional simple stimuli and gain deeper insights into how the brain processes and predicts changes in complex visual environments.
My academic journey began with a B.Sc. in Computer Engineering from Babol Noshirvani University of Technology, Mazandaran, where I developed a strong foundation in computational and analytical thinking. For my undergraduate project, I worked with EEG-based emotion recognition using Deep Reinforcement Learning, which sparked my long-term interest in understanding how the brain encodes and processes cognitive and affective information.
My growing fascination with how the mind works naturally led me toward neuroscience. Why are we exceptionally good at certain tasks yet struggle with others? Can understanding neural mechanisms help us enhance our cognitive abilities or design better artificial systems?
I believe neuroscience holds the key to answering such questions. By studying the brain’s computational principles (i.e. predictive coding, attractor dynamics, neuromodulation), we can bridge the gap between biological intelligence and artificial intelligence.
I’m particularly passionate about developing neuro-inspired computational models that draw on biological principles to build more interpretable, robust, and adaptable AI systems. By grounding machine learning in the mechanisms of the human brain, I hope to contribute to both neuroscience and next-generation AI research, advancing our understanding of cognition while helping shape intelligent systems that are as insightful as they are powerful.
Research Interests
Computational Neuroscience
NeuroAI
Vision Science
Interpretable AI
Education
MSc in Neuroscience at University of Western Ontario, London, ON, 2025–Present
MSc in Artificial Intelligence Engineering at University of Tehran, Tehran, GPA 19.12/20, 2021–2024
BSc in Computer Engineering at Babol Noshirvani University of Technology, Mazandaran, GPA 17.38/20, 2016–2021
Languages
Persian, English
Hobbies and Interests
Reading, Movies, Cooking, Gymnastics, Ballet, Painting