Haida Asif

PROFESSIONAL PROFILE Haida Asif is a detail-oriented Electrical Engineering student at the National University of Sciences and Technology (NUST), Islamabad, expected to graduate in 2026, with a strong academic foundation in embedded systems, circuit design, signal processing, and software–hardware integration, and a focused specialization in Computer Vision and Machine Learning. She has extensive project-based experience designing and implementing systems using microcontrollers, sensors, and embedded software, working independently and in team-based academic settings with strong collaboration and troubleshooting skills. Her project portfolio spans automation, control systems, robotics, and assistive technologies, including automatic street lights using solar panels, fingerprint- based door lock systems, automatic fan speed controllers, smart sticks for the visually impaired, automatic sun-following solar panels, human-following robots, and digital even/odd bit parity generators, alongside advanced ML/CV projects such as a voice-based emotion detection model, a driver fatigue detection system (awarded Best Simulation), and a real-time Pakistani Sign Language interpreter as her Final Year Design Project, enabling two-way translation between sign language, text, and audio. She has completed rigorous coursework in Circuit and Network Analysis, Microprocessors, Electronics I & II, Digital Logic, Control Systems, Digital Signal Processing, and Computer Communication Systems, and further strengthened her expertise through internationally recognized certifications in ML and CV from Harvard (edX), Columbia and Stanford (Coursera). Complementing her technical profile, she has held leadership and management roles in university societies, reflecting strong organizational ability, adaptability, and a strong commitment to continuous learning and impactful, real-world engineering solutions. EDUCATION Electrical Engineering SEECS , Islamabad , 2.22 (4) INTERNSHIP EXPERIENCE ONT Lab SEECS 16-Jun-2025 - 16-Sep-2025 Completed a 3-month internship at the ONT Lab, SEECS, where I designed and implemented an optical transceiver based on DQPSK modulation, incorporating bit scrambling and key-based encryption/decryption to secure optical communication and mitigate eavesdropping. FINAL YEAR PROJECT SignLink SignLink is an AI-powered mobile application that translates sign language gestures into spoken words in real time. It uses computer vision and a trained LSTM model to recognize hand movements and convert them into meaningful phrases. Designed to bridge the communication gap for the deaf and hard-of-hearing community, SignLink enables seamless interaction between sign language users and non-signers. TECHNICAL EXPERTISE Computer Vision, Machine Learning & Robotics Strong technical expertise in Computer Vision and Machine Learning with hands-on experience in developing real-world intelligent and robotic systems. Built multiple ML- and CV-based projects including a voice-based emotion detection model, a driver fatigue detection system using computer vision and machine le ...

Haida Asif is a detail-oriented Electrical Engineering student at the National University of Sciences and Technology (NUST), Islamabad, expected to graduate in 2026, with a strong academic foundation in embedded systems, circuit design, signal processing, and software–hardware integration, and a focused specialization in Computer Vision and Machine Learning. She has extensive project-based experience designing and implementing systems using microcontrollers, sensors, and embedded software, working independently and in team-based academic settings with strong collaboration and troubleshooting skills. Her project portfolio spans automation, control systems, robotics, and assistive technologies, including automatic street lights using solar panels, fingerprint- based door lock systems, automatic fan speed controllers, smart sticks for the visually impaired, automatic sun-following solar panels, human-following robots, and digital even/odd bit parity generators, alongside advanced ML/CV projects such as a voice-based emotion detection model, a driver fatigue detection system (awarded Best Simulation), and a real-time Pakistani Sign Language interpreter as her Final Year Design Project, enabling two-way translation between sign language, text, and audio. She has completed rigorous coursework in Circuit and Network Analysis, Microprocessors, Electronics I & II, Digital Logic, Control Systems, Digital Signal Processing, and Computer Communication Systems, and further strengthened her expertise through internationally recognized certifications in ML and CV from Harvard (edX), Columbia and Stanford (Coursera). Complementing her technical profile, she has held leadership and management roles in university societies, reflecting strong organizational ability, adaptability, and a strong commitment to continuous learning and impactful, real-world engineering solutions.