Muhammad Altaf

Completed an MS in Computer Engineering with a focus on advanced machine learning, deep learning, and data-driven system design. The program emphasized theoretical foundations and practical applications in areas such as computer vision, algorithm optimization, and intelligent system development, equipping graduates with the skills required for research and industry innovation in AI and data science. Key Projects Theft Detection System (Odyssey Analytics) Developed a real-time surveillance solution using pose estimation and action recognition. KFC Drive-Thru Automation (Computer Vision) Built a vision-based system for vehicle detection and customer interaction tracking. NVIDIA Omniverse – Synthetic Data Generation Generated synthetic datasets for training AI models in simulated 3D environments. Weapon Detection for Hospitals (YOLOv5 + AWS) Deployed an object detection system for hospital security using YOLOv5 on AWS. Cricket Analytics App (Computer Vision) Built an app to track ball trajectory and player performance using CV techniques. LLM-Based QA System Created a multi-document QA tool using LLaMA 3.1, FAISS, LangChain, and Streamlit. Medical Coding Automation Designed an NLP system to extract ICD-10 and CPT codes from patient PDFs.

Electrical Engineering graduate with a strong foundation in signals, systems, and automation. Graduated with a 3.5/4.0 CGPA, skilled in applying engineering principles to real-world problems.