Muhammad Faseeh Khattak

I’m a Software Engineering student with a strong academic foundation and practical experience across full-stack development, database systems, and applied AI. I build intelligent, scalable solutions using Python, FastAPI, React, and large language model APIs.

In my Software Engineering Intern role, I supported enterprise-level software development alongside senior engineers. I worked with relational databases using SQL, contributed to debugging and code reviews, and participated in software testing while learning the real-world SDLC process.

My featured work is DENTIVISE, an AI clinical diagnostic platform that combines computer vision with multimodal LLM capabilities for automated dental radiograph analysis. I trained a YOLOv11 object detection model in PyTorch on 1,400+ annotated images, built a scalable FastAPI backend for secure ingestion and AI inference orchestration, and integrated Google Gemini multimodal API for context-aware report generation. I also delivered a responsive React interface with automated PDF export using jsPDF and html2canvas.

I’m actively transitioning into AI/ML engineering with hands-on exposure to computer vision, multimodal AI systems, and conversational AI development. I’m seeking internship opportunities where I can contribute to real-world AI-driven systems while strengthening both machine learning and software engineering skills—whether through projects like my Streamlit + Gemini learning assistant or my Python + Gemini interview simulation chatbot.