AI Engineering
Building and evaluating machine-learning and computer-vision workflows, with attention to explainability, robustness, and practical use.
ABOUT
Engineering practical AI systems with research-driven thinking.
I'm Ghayda N. Ja'afreh, an AI Engineer and Data Scientist working across machine learning, computer vision, data science, backend integration, and applied research. I'm most interested in projects where careful experimentation and practical engineering need to work together.
HOW I WORK
From experiments to understandable, usable workflows.
My portfolio reflects a deliberately broad technical path: model comparison and evaluation, computer-vision applications, interactive AI tools, secure backend workflows, and research-oriented projects. The common thread is a preference for systems that can be inspected, tested, and explained rather than treated as black boxes.
I value reproducibility, clear evidence, responsible communication of results, and implementation choices that match the actual problem. That approach carries from academic work into software and applied AI projects.
Research
Working through controlled experiments, model evaluation, academic problem framing, and evidence-driven technical communication.
Applied Systems
Connecting models with interfaces, APIs, secure workflows, and software components so experiments become usable systems.
TECHNICAL FOCUS
What I work with.
A cross-disciplinary toolkit connecting AI research, engineering, data, computer vision, and software integration.
AI & Machine Learning
Python · PyTorch · TensorFlow · scikit-learn
Computer Vision
OpenCV · U-Net · Segmentation · OCR
Backend & APIs
FastAPI · REST APIs · Authentication · Logging
Data Science
Pandas · NumPy · SQL · Model Evaluation
Engineering
Git · Testing · Debugging · Documentation
Cloud & Tools
Azure · Jupyter · Kaggle · Gradio
EXPLORE THE WORK