BSc in Informatics Technology Engineering — specialization in Artificial Intelligence, Arab International University, Damascus, Syria (2025).
I build deep learning systems for medical imaging and clinical AI. My work combines computer vision, clinical NLP, multimodal search, and explainability — with a focus on building AI that clinicians can actually trust and use.
- Medical imaging — CT scan lung cancer detection, chest X-ray multi-label classification, Grad-CAM explainability
- Multimodal AI — CLIP-based semantic search over medical literature using FAISS
- Clinical NLP — symptom extraction, negation detection (ConText), biomedical embeddings
- VLM benchmarking — evaluating BiomedCLIP, PubMedCLIP, BioCLIP on ROCO medical dataset
- Speech AI — medical audio transcription using wav2vec2
- Backend — 4 production e-commerce systems built with Laravel + MySQL
| Project | Description | Stack |
|---|---|---|
| lung-cancer-ct-detection | EfficientNetB1 fine-tuned on LUNA16 CT scans · AUC 0.921 · Grad-CAM explainability | TensorFlow · Keras |
| chest-xray-classification | DenseNet-121 vs EfficientNetB1 · NIH ChestX-ray14 · 14 disease labels · Mean AUC 0.841 | PyTorch |
| medical-ai-multimodal-system | Speech → NER → FAISS search → VLM benchmarking · End-to-end medical AI pipeline | CLIP · FAISS · wav2vec2 |
AI / ML
Medical AI
Languages
Backend & Tools
- BSc graduate in AI Engineering — Arab International University (2025)
- Open to remote AI/ML roles and international opportunities
- ChatGPT Prompt Engineering for Developers
- Git & GitHub Fundamentals for Software Developers
"Building AI that clinicians can trust — not just AI that performs."