Hamza Amin

Developed and deployed machine learning algorithms for strategic decision-making. Led ETL processes to ensure streamlined data availability. Created interactive dashboards using Power BI, Tableau, and Qlik. Conducted Python and SQL analysis to derive actionable insights. Automated data workflows, improving accuracy by 50%. Developed Python ETL scripts, reducing processing time by 40%. Collaborated cross-functionally to align ETL with organizational goals.

Developed state-of-the-art object detection, image segmentation, and feature extraction algorithms. Implemented and optimized CNN model for detecting icing on wind turbine rotor blades using colored and infrared images. Leveraging data analytics techniques and CNN models for detecting discrepancies in 3D printed shoes. Trained and deployed models on Microsoft Azure. Proficient in Python and Object-Oriented Programming. Expertise in object detection using OpenCV. Performed data analysis using Pandas and SQL.

Thesis: Vision-based Identification of Steel Coils using Deep Learning Methods Developed and implemented object detection and instance segmentation Deep Learning algorithms for steel coil identification. Conducted a feasibility study on feature extraction via image segmentation. Project: Transfer Learning using YOLOv3 for Object Detection in Thermal Images Implemented and leveraged transfer learning with YOLOv3 for real-time object detection in thermal images, enhancing railway safety.

Final Year Project: Android Based Wheelchair with Wireless Home Automation