Tarek Amr

I’m an Artificial Intelligence Engineering undergraduate with hands-on experience building end-to-end AI applications across computer vision, retrieval-augmented generation, data engineering, and business intelligence. I focus on reproducible model-training and evaluation pipelines, benchmarking production candidates for accuracy and latency, and deploying user-facing apps with FastAPI and Streamlit.

In training, I completed the NVIDIA DLI Summer Training Program in Generative AI (Beginner Level), including 17 hours of LLM application development and RAG practice. Through projects, I’ve built a local-first RAG assistant with grounded-answer guardrails, a road-damage object detection pipeline with benchmarking and deployment, and data pipelines and dashboards in Power BI and SQL Server to turn large datasets into actionable insights.