Muhammad Ammar Bin Akram

PROFESSIONAL PROFILE Aspiring computer vision and deep learning engineer with hands-on experience in developing AI systems for real-world applications, including automated snooker scoring and mango detection. Skilled in Python, OpenCV, PyTorch, TensorFlow, and YOLO, with experience in deploying models on edge devices like Raspberry Pi. Seeking opportunities to apply technical expertise to innovative projects in computer vision and AI, while continuing to grow in advanced deep learning and real-time system development. EDUCATION Bachelors of Science in Computer Science School of Electrical Engineering and Computer Science , Islamabad , 3.35 (2022) INTERNSHIP EXPERIENCE DataQuartz 23-Jun-2025 - 18-Aug-2025 Worked on the Snooker Vision Project, focused on automating the complete snooker game using deep learning and computer vision, Developed features for player turn management and real-time score calculation, Implemented foul detection logic based on ball interactions and shot analysis , Designed potting detection mechanisms for accurate game event tracking RoadGauge 11-Aug-2025 - 31-Oct-2025 Worked on tracking road assets using advanced computer vision models, Contributed to the development of an automated road inspection system, Applied 2D image processing techniques for visual analysis of road conditions, Utilized deep learning models to improve detection and tracking accuracy FINAL YEAR PROJECT ExportEdge AI Designed and implemented an edge-AI solution to automate mango quality inspection and export decision-making. The system uses deep learning for mango classification and disease segmentation, combined with an LLM (RAG-based) to recommend optimal export prices and destination countries, deployed on Raspberry Pi. TECHNICAL EXPERTISE Computer vision and Deep learning Experienced in designing and implementing computer vision systems for real-world applications, including object detection, image classification and segmentation, tracking, and automated inspection. Skilled in using Python, scikit-learn, numpy, pandas, OpenCV, PyTorch, TensorFlow, and YOLO fro developing AI so ...

Aspiring computer vision and deep learning engineer with hands-on experience in developing AI systems for real-world applications, including automated snooker scoring and mango detection. Skilled in Python, OpenCV, PyTorch, TensorFlow, and YOLO, with experience in deploying models on edge devices like Raspberry Pi. Seeking opportunities to apply technical expertise to innovative projects in computer vision and AI, while continuing to grow in advanced deep learning and real-time system development.