Fayad Alman
Data Visualization Officer
Markham, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolFayad Alman is a Machine Learning engineer based in Markham, Ontario with 3 years of hands-on experience building ML models and APIs in Python. He has practical expertise with PyTorch, TensorFlow, JAX, and Ivy, and contributed to transpiling major libraries (including converting much of Kornia into the Ivy framework) to improve cross-framework compatibility and device handling. At Ontario Power Generation he deployed an RNN for predictive maintenance with 96% accuracy and built PowerBI dashboards to surface outage patterns, demonstrating a blend of model engineering and data visualization. He has led small contributor teams at Unify and helps run community events at Toronto Metropolitan University, showing both technical leadership and outreach. Outside work he’s a family-oriented Newcastle fan who channels curiosity into automation projects for industries like agriculture and medicine.
3 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Computer Science, 3.85 out of 4.33, Bachelor of Science - BS, Computer Science, 3.85 out of 4.33 at Toronto Metropolitan UniversityHigh School Diploma, High School Diploma at Middlefield Collegiate Institute
English, Bengali
Github Skills (10)
ivy10
machine-learning10
deep-learning10
python10
converter10
numpy9
jax9
tensorflow9
neural-network9
pytorch9
Programming languages (1)
Github contributions (5)
ivy-llc/ivy
Jan 2023 - Jan 2023
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:59 reviews, 2 commits, 91 PRs in 1 day
Contributions summary:Fayad contributed to the `ivy` repository, which focuses on converting machine learning code between frameworks. Their commits primarily involve updating and modifying the `device.py` file, which likely handles device management (CPU/GPU) within the framework. They also added copy arguments to the `manipulation.py` file, suggesting improvements to data manipulation functionalities. These changes indicate a focus on framework internal workings and potentially improving the efficiency or capabilities of the framework for machine learning tasks.
pythontensorflowframework-learningtemplatedata-science
Fayad-Alman/ivy-1
Dec 2022 - Feb 2023
The Unified Machine Learning Framework
Contributions:4 PRs, 144 pushes, 17 branches in 1 month
pythondata-sciencedeep-learningmachine-learningframework-learning
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