Ellie Nasr

MSc Biometrics and Intelligent Vision student with strong skills in machine learning, deep learning, computer vision, and biomedical data analysis. Experienced in Python development, GUI design with PyQt5, database management, and real-time signal and image processing and Llma. Passionate about building practical, user-focused AI applications for healthcare, imaging, and intelligent systems.

• Data Capture and Processing: ECG analysis: signal energy, variance, SNR, R-peak detection. Speech signal analysis: PSD computation, windowing functions, FIR/IIR filter application.
• Software Integration: LLaMA-3 Chat GUI App: PyQt5 chatbot for local LLaMA-3 inference. SQL Database: Created and queried person/address tables. REST API: Flask API for CRUD operations on MySQL records. Parallel Processing: Multi-threaded image resizing benchmark. Transfer Learning: Image classification with fine-tuning of pre-trained models.
• Digital Image Processing: Thresholding & Histograms: Manual stretching, Otsu’s method. Morphological Operations: Erosion, Dilation, Skeletonization. Edge Detection: Sobel, Prewitt, Canny, Laplacian. Medical Image Segmentation: Liver extraction using adaptive thresholding. Object Classification: Shape-based feature extraction for card symbols. Distance Transforms: Euclidean, Chessboard, Cityblock.