About Me

I am a detail-oriented professional who brings a solid foundation in machine learning and statistics. With +4 years of hands-on experience in Python programming, I’ve honed my skills in data manipulation, exploration, and maintenance of enterprise data models. I am highly skilled in all aspects of data analysis, including data pre-processing, data manipulation, feature extraction, statistical analysis, and data visualization techniques. I am a dedicated and adaptable professional with excellent communication skills, adept at fitting into various workplaces and collaborating effectively within teams.

Professional Experiences

Research Assistant

         • Engaging in collaborative research efforts within the framework of a large-scale project (OMMABA), taking place at McGill and Western Universities
        • Utilizing various data collection methodologies, including the acquisition of behavioral, EEG, and fMRI data, from cohorts of healthy volunteers
        • Demonstrating proficiency in data pre-processing, cleaning, and analysis, ensuring the reliability of collected datasets

Machine Learning Research Intern

         • Extracted RGB and Optical flow from videos generated using THINGS database
        • Assessed the performance of action recognition models (two-stream I3D ConvNet, R(2+1)D ConvNet, and ConvLSTM) under rapid target presentation
        • Formed Representational Dissimilarity Matrices (RDMs) and conducted Representational Similarity Analysis (RSA) to compare model performance and and brain response patterns
        • Highlighted CNN limitations in mimicking brain processing in rapid visual tasks and proposed RNNs as a better approximation

Graduate Research Assistant

        • Proposed a novel hypothesis about object recognition, suggesting the crucial role of recurrent processing in visual system
        • Conducted an independent experiment and collected EEG data from human volunteers to investigate the neural dynamics of image processing
        • Performed pre-processing, cleaning, and manipulation on 100 GB collected EEG data
        • Leveraged machine learning techniques such as Multivariate Analysis and bootstrapping to analyze pre-processed data
        • Utilized inferential statistical analysis to confirm the proposed hypothesis

Teaching Assistant

        • Held Python tutorials for Computer Science Fundamentals and managed over 40 students during these tutorial sessions
        • Collaborated closely with course instructors to prepare the course material

Publications and Projects

Presentations

Awards

• [Sep. 2021] BrainsCAN Scholarship
• [Sep. 2016] National Elites Foundation’s Fellowship
• [Sep. 2016] Ranked 16th in the Iranian National University Entrance Exam