AI Engineer - Est. 2026
I am a Computer Science and Artificial Intelligence undergraduate at Misr University for Science and Technology, where I focus on software development, AI algorithms, data science, and neural networks. My passion lies in designing and deploying end‑to‑end machine learning and deep learning models for real‑world applications. I have built award‑winning projects such as Dignova, which secured 1st place at the YTA‑AI Competition, and contributed to research on multi‑task oral cancer detection. Beyond academia, I am actively expanding my practical AI skills through an AI Diploma with Instant and certifications from NVIDIA and Huawei. I thrive in collaborative environments, leveraging my strong technical foundation in Python, PyTorch, and cloud‑scale data pipelines to solve complex problems. I am eager to bring my expertise in AI model development, full‑stack engineering, and automation to a forward‑thinking organization.
1yrs
Building products
2
Featured projects
1×
Roles shipped
30
Tools in kit
The path
Digital Egypt Pioneers Initiative (DEPI)
Developing practical skills in AI automation and applying AI‑driven approaches to real‑world workflows. Building experience with AI tools, automation‑oriented problem solving, and integrating intelligent solutions into practical tasks.
Misr University for Science and Technology (MUST)
Focus: Software Development, AI Algorithms, Data Science, Neural Networks
NVIDIA
Huawei
NTI (National Telecommunication Institute) & ITIDA
The British University in Egypt (BUE), School of Continuing Education
American Board of Professional Studies (ABPS)
Google Developer Student Clubs (GDSC) at MUST
IT Sharks Training Center
Toolbox
2 collaborations. Each one shipped and still running.
Built for the Egyptian Anti‑Drug Fund. Developed a full‑stack platform comprising a Flutter mobile app, React.js admin dashboard, and NestJS backend. Implemented triple‑guard authentication, TypeORM entities, Redis TTL caching, and Haversine proximity detection. Extended the platform with an AI‑powered feedback summarization microservice using FastAPI and Ollama (Qwen2.5 7B).
Awarded 1st Place – Best Application at the YTA‑AI Competition. Solely designed, trained, and deployed DL models: DenseNet‑121 V2 for chest X‑ray multi‑label pathology classification and EfficientNet‑B4 with a custom Attention Gate for bone fracture multi‑class classification. Applied cosine LR scheduling, class‑weighted loss, data augmentation pipelines, and ImageNet‑pretrained backbones fine‑tuned for medical imaging.
Currently
Working as Participant — AI Automation Track at Digital Egypt Pioneers Initiative (DEPI).
Available
Taking on projects for Booking Q4 2026.
Next chapter
Booking Q4 2026. Tell me what you're building, I reply within a day.
ayafawzyatya78@gmail.com