Yassine Ouardani

– Designing OCR/NLP pipelines for medical document processing using Python and FastAPI. – Developing chatbot systems based on Retrieval-Augmented Generation (RAG) with Elasticsearch. – Creating AI agent systems with LangChain to monitor and analyze connected health device data. – Developing innovative food segmentation APIs using computer vision and multimodal models. – Formatting and managing sensor data according to HL7 FHIR standards using WebSocket for streaming data, combined with Kafka, Logstash, Elasticsearch, and Grafana for real-time visualization. – Managing microservices architecture with Docker and Nginx, ensuring consistent environments.

– Trained YOLO model on 50k+ industrial vehicle data, created a pipeline to automatically annotate. – Built a microservices app for vehicle–employee distance estimation (improving safety by 25%), with confidential filtering (data security +30%) and danger zone detection (risk prevention +20%).

– Developed a CNN-based model for Arabic calligraphy classification using VGG16 architecture. – Tools Tech: Python, PyTorch, Pandas, NumPy, CNN, CUDA, Git, GitHub.