Muhammad Moiz Akram

Electrical Engineering graduate specializing in AI/ML, autonomous multi-modal agent frameworks, and custom deep learning solutions. Proven track record building end-to-end intelligent systems—ranging from ReAct-based GPT-4 agents with multi-modal 3D-CNN/ResNet backends to high-throughput RAG architectures using ChromaDB and FAISS. Skilled in developing scalable FastAPI microservices, predictive diagnostics models, and production-ready Streamlit dashboards. Focused on delivering high-performance, benchmarked, and reliable software for complex engineering and data problems.