Syed Shaheer Raza Naqvi

PROFESSIONAL PROFILE Electrical Engineering undergraduate at NUST with a multidisciplinary skill set spanning embedded systems, digital design, and machine learning. Experienced in developing real-time computer vision applications, including a sign language recognition system using LSTM models and MediaPipe. Strong background in C++/Python, hardware-software integration, and engineering simulation tools, complemented by industrial exposure at Pakistan Airports Authority (CNS). EDUCATION BE Electrical Engineering School of Electrical Engineering and Computer Science , Islamabad , 2.57 (2026) INTERNSHIP EXPERIENCE Pakistan Airports Authority 03-Jul-2025 - 17-Aug-2025 I completed a six-week internship at the Communication, Navigation, and Surveillance (CNS) Department of Pakistan Airports Authority (PAA) at Multan International Airport. During this internship, I gained hands-on exposure to the operation, monitoring, and basic maintenance of critical aviation CNS systems, including air-ground communication systems, navigation aids, surveillance and monitoring equipment, and supporting IT and power infrastructure. I also developed an understanding of system redundancy, fault monitoring, regulatory compliance, and the role of CNS systems in ensuring safe, reliable, and efficient air traffic management. FINAL YEAR PROJECT SignLink: Bridging Communication Through Vision and AI Developed a real-time sign language recognition system using a React Native mobile app and a Flask-based server. Integrated MediaPipe for feature extraction and trained an LSTM model on custom gesture dataset for gesture-to-text conversion. TECHNICAL EXPERTISE Expertises in Embedded Systems, Machine Learning and Computer Vision I possess strong technical expertise in electrical testing, troubleshooting, and circuit design, with hands-on experience in embedded systems development. I am proficient in C++ and Python programming and have extensive experience working with microcontrollers and FPGAs, including hardware description using V ...

Electrical Engineering undergraduate at NUST with a multidisciplinary skill set spanning embedded systems, digital design, and machine learning. Experienced in developing real-time computer vision applications, including a sign language recognition system using LSTM models and MediaPipe. Strong background in C++/Python, hardware-software integration, and engineering simulation tools, complemented by industrial exposure at Pakistan Airports Authority (CNS).