Omid Heidari is a research-driven machine learning and data science practitioner with seven years of experience spanning industry roles at CIBC and multidisciplinary research positions at Concordia, UBC, and VITA. Currently a PhD student in Industrial Engineering at Concordia (and previously an MS in Computer Science), he combines academic rigor with practical applied work—ranging from teaching assistantships to data research analysis in medical and engineering domains. His GitHub contributions show hands-on model development and ensembling techniques, including a course-focused ML repo where he implemented voting classifiers and exploratory feature analysis. Comfortable moving between research and production settings, he has collaborated with diverse supervisors and labs on projects that bridge algorithm development and real-world data. Colocated in Montreal, he brings a blend of pedagogy, research mentorship, and industry experience that positions him to translate novel ML methods into impactful applications.
7 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Industrial Engineering, Doctor of Philosophy - PhD Industrial Engineering at Concordia University
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Islamic Azad University
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at University of Zanjan
Machine Learning Course, Sharif University of Technology
Role in this project:
Data Scientist
Contributions:29 commits, 4 PRs, 27 pushes in 3 months
Contributions summary:Omid's commits focus on developing and implementing machine learning models within a course related to machine learning. The primary contribution involves building a classification model to predict a target variable based on tabular data, likely leveraging techniques such as label encoding, data exploration, and model training with various algorithms, including voting classifiers (Logistic Regression, Decision Tree, and SVM). The commits suggest an interest in using model ensembling methods. The user also performed data exploration by creating a heatmap to view correlations between features.
Contributions:13 releases, 2 commits, 7 PRs in 5 months
redisredis-serverkeysredis-client
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.
Request Free Trial
Omid Heidari - Research Assistant at Concordia University