Muhammad

Mobile application Developer

codingpanel • Período integral

Jan 2026 - Present • 4 mos

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Mobile Application Development

CITY UNIVERSITY (Summer Internship Program ‑ Peshawar ) • Meio período

Sep 2025 - Oct 2025 • 1 mo

Completed a Summer Internship Program at City University, where I worked on multiple real-world projects focusing on mobile application development, system design, and machine learning integration. The internship strengthened my practical skills in Flutter, backend integration, data handling, and ML-powered applications. Key Projects: Learning Management System (LMS) Developed a comprehensive Learning Management System to streamline online education and course management for City University. The system allows students to access lectures, assignments, and grades through a clean and user-friendly interface. Faculty members can create and manage courses, upload learning materials, and monitor student progress efficiently. Integrated dashboards and notification features to enhance communication and improve the overall learning experience. Liver Disease Detection Application (Flutter + Machine Learning) Designed and developed a liver disease detection mobile application using Flutter and TensorFlow Lite. The app enables users to enter medical parameters and receive real-time health predictions. Achieved approximately 90% prediction accuracy, ensuring reliable and consistent results. Emphasized intuitive UI/UX design to provide a seamless, accessible, and user-friendly experience.

Flutter Developer

TRI BYTE SOLUTION • Período integral

Jun 2025 - Sep 2025 • 3 mos

During my time at Tri Byte Solution, I worked as a Flutter Developer, where I designed and developed multiple mobile applications with a strong focus on performance, scalability, and user experience. I collaborated with cross-functional teams to build real-world solutions using Flutter, Firebase, REST APIs, GPS services, and Machine Learning integration. Key Projects: My Drive (Ride-Hailing Application) Developed a full-featured ride-hailing mobile application that connects passengers with nearby drivers in real time. The app includes GPS-enabled live location tracking for accurate pickup and drop-off points, secure and transparent payment gateway integration, and a smooth booking experience. The solution was designed to provide efficient, affordable, and reliable transportation while ensuring high usability and performance. Solar Panel Anomaly Detection System (Flutter + Machine Learning) Built a smart anomaly detection system for solar panels that identifies faults such as cracks, dust accumulation, bird droppings, and other irregularities. The application integrates machine learning models to analyze images and detect performance issues in real time. This system enables early fault detection, improves energy efficiency, reduces maintenance costs, and extends the overall lifespan of solar panels. Overall Contributions: Developed and maintained multiple Flutter applications Integrated machine learning models into mobile apps Implemented real-time data handling and GPS services Focused on clean architecture, UI/UX, and performance optimization