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Schedule Interview NowMy name is Fadi F. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Artificial Intelligence, Desktop Application, Machine Learning, Deep Learning, Natural Language Processing, etc.. I hold a degree in Master's degree, Bachelor's degree. Some of the notable projects I’ve worked on include: KidzPay – Smart Fintech & Parental Control System with NFC Integration, ImageTriSplit – Fast Image Dataset Split Tool for Deep Learning, GreyVive – AI-Powered Image Colorization Model. I am based in Tebessa, Algeria. I've successfully completed 3 projects while developing at Softaims.
I specialize in architecting and developing scalable, distributed systems that handle high demands and complex information flows. My focus is on building fault-tolerant infrastructure using modern cloud practices and modular patterns. I excel at diagnosing and resolving intricate concurrency and scaling issues across large platforms.
Collaboration is central to my success; I enjoy working with fellow technical experts and product managers to define clear technical roadmaps. This structured approach allows the team at Softaims to consistently deliver high-availability solutions that can easily adapt to exponential growth.
I maintain a proactive approach to security and performance, treating them as integral components of the design process, not as afterthoughts. My ultimate goal is to build the foundational technology that powers client success and innovation.
Main technologies
2 years
1 Year
1 Year
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Potentially possible
Sofrecom Algérie
KidzPay is a smart fintech solution that helps parents monitor and control their children’s spending using a mobile app and NFC-enabled bangle. Parents receive instant purchase notifications, while sellers use a dedicated app to scan the bangle and process transactions. The system enhances child safety, promotes financial responsibility, and prevents harmful purchases through real-time oversight and smart controls.
ImageTriSplit is a fast, open-source Python tool that automates splitting image datasets into train, validation, and test folders for deep learning. It supports custom split ratios, ensures randomized distribution, and is compatible with frameworks like TensorFlow and PyTorch. Designed for simplicity and speed, it helps AI developers save time and avoid manual errors during dataset preparation.
GreyVive is an advanced deep learning project developed to automatically colorize grayscale images using artificial intelligence. Leveraging convolutional neural networks (CNNs), GreyVive analyzes and reconstructs realistic colors in black-and-white photos without human intervention. The model was trained on diverse datasets to understand contextual color patterns and enhance visual accuracy. This solution is useful in restoring historical images, artistic applications, and image enhancement tools.
Master's degree in
2024-01-01-2026-01-01
Bachelor's degree in
2020-01-01-2024-01-01