My childhood curiosity about automatic machines as simple as a watch transformed by time to a passion for designing automated processes as complex as computational models of cognition. I started my academic career by studying computer engineering. During the course, I improved my mathematical sense of data processing and got familiar with algorithm design beside principles of circuits such as electric, electronic, and digital.Getting to know the nature of the human mind, my enthusiasm to study the brain as a unique data processor grew. I started a bachelor course in neuroscience. During the course, I learned the principles of human psychology and cognition and the biological aspects of mind. Bringing together computational and psychological knowledge, I did a project for my bachelor thesis, which aimed to simulate visual cortex functions by deep networks. During this project, I studied machine learning and different computational models of cognition.I continued neuroscience study to the master level, where I deepened my understandings of the neural aspects of cognition beside the principles of neuropsychological disorders and rehabilitation. The last year of the course, I was involved in neuroimaging data analysis. I ran a DTI data analysis project of alcohol dependence in mouse models where I got familiar with the concepts of neuroimaging data preprocessing and statistical analysis. For my master thesis, I analyzed a set of individual DTI data which concerned the study of the interaction between intelligence and creativity at the neural level.In summary, I am passionate about the brain, data science, and artificial intelligence. My computational background with a technical slant along with psychological knowledge with a neuroscience perspective, let me take part in brain science research activities with a quantitative approach.