I’m Aydin Abedinia, a Senior Engineering Manager with a passion for software engineering, machine learning, and research. Over the past decade, I’ve been at the forefront of building resilient backend architectures and delivering end-to-end machine learning solutions that drive real-world impact. My expertise spans across multiple programming languages including Go, PHP, Python, and, more recently, Rust—a language that aligns perfectly with my vision of creating high-performance, scalable systems.
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Software Architecture: I specialize in designing robust and scalable backend systems that stand the test of time. My approach ensures that these systems are not only high-performing but also maintainable and adaptable to future needs.
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Machine Learning & MLOps: My experience covers the entire ML lifecycle, from data preprocessing and model training to deployment and monitoring. I’m committed to bridging the gap between data science and production systems, ensuring that models are as reliable as they are accurate.
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Decision Trees & Semi-Supervised Learning: My work in these areas has led to innovative algorithms that enhance predictive accuracy and model robustness, particularly in challenging environments with limited labeled data.
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Deep Learning & Boosting Techniques: I am deeply involved in advancing the state of deep learning and boosting methods, integrating cutting-edge research into practical, scalable solutions.
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SemiCart: A semi-supervised algorithm that leverages test data weights to significantly enhance classification accuracy. It represents the cutting edge of algorithmic innovation in semi-supervised learning.
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Distance-Based-Weighting: Distance based wighting to calculate weights of training records, considering the distance from test set.
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Rust Decision Tree: This Rust package implements decision tree classifiers with a focus on both Gini impurity and entropy-based information gain, blending efficiency with precision.
Feel free to reach out to me through any of the following platforms:
