Nayab Nazar

PROFESSIONAL PROFILE A highly motivated and research driven final year Electrical Engineering student with a minor in Artificial Intelligence, specializing in autonomous systems, nonlinear control, and edge AI. Possesses hands-on experience in designing and implementing advanced control algorithms for UAVs/USVs, developing real-time computer vision models for edge deployment, and leading multi-agent robotic projects for environmental monitoring. Demonstrated ability to conduct end-to-end research, from simulation and optimization to hardware-in-the-loop testing and field deployment. Have a a strong publication record including conference papers and journal submissions. Proven leadership through founding technical initiatives, managing interdisciplinary teams, and serving as an elected student representative. Seeking to apply expertise in robotics, AI, and embedded systems to innovative R&D or engineering roles in autonomous technology. EDUCATION Higher secondary school education Govt Degree college Tararkhel, AzadKashmir , Tararkhel, Azadkashmir , 1072/1100 (2022) Electrical Engineering SEECS(School of Electrical Engineering and Computer Science) NUST-H12 , Islamabad , 3.2 (2026) INTERNSHIP EXPERIENCE Research Assistant — Digital Twin Lab, SINES ( NUST) 01-Jul-2025 - 01-Jun-2026 Developing and deploying a fleet of three autonomous Unmanned Surface Vehicles (USVs) for persistent, real-time water quality and environmental monitoring across rivers, lakes, ponds and coastal waters. The system integrates modular payloads and on-board sensor-fusion (GPS/IMU/camera/sonar) to deliver high fidelity telemetry. USVs operate under hybrid swarm control architectures— centralized mission orchestration and leader–follower or leaderless decentralized consensus—enabling cooperative task allocation, formation, control, adaptive path-planning and robust inter-vehicle coordination. Communications include ground station USV telemetry and low-latency inter-USV links for real-time coordination; emphasis is placed on fault-tolerance, energy-aware mission scheduling, hardware-software integration, and hardware-in-the-loop plus field validation. The mission objective is scalable, resilient autonomous monitoring with extensibility toward advanced maritime sensing and multi-mission applications.It is funded by NESCOM and RIC NUST. CSN(Communication Systems and Networking Lab) SEECS-NUST 01-Jun-2025 - 01-Sep-2025 Focused on Edge AI Deployment and UAV Communication Systems ML Model Deployment on Edge: Optimized and deployed real- time fire and smoke detection models (YOLO/UNet variants) on embedded platforms, using TensorRT for inference acceleration on NVIDIA Jetson devices. Edge Computing Pipeline: Developed a full sensor-processing pipeline on UAVs, integrating camera feeds with onboard AI inference for immediate threat detection without cloud dependency. Communication System Testing: Assisted in testing and implementing robust communication protocols between UAVs and ground stations to ensure stable data transmission in remote environments. System Integration Support: Contributed to integrating the AI detection module with the ground control software and alerting system used in the lab’s ongoing UAV projects. Undergraduate Researcher — Graduate Research Complex, SEECS – NUST 15-Sep-2024 - 15-Sep-2025 Conducting advanced research on nonlinear control of underactuated bicopter UAVs, focusing on robust and optimized controller design. Authored a research paper titled “Advanced Optimized Nonlinear Control of Bicopter UAVs” currently under peer review.

A highly motivated and research driven final year Electrical Engineering student with a minor in Artificial Intelligence, specializing in autonomous systems, nonlinear control, and edge AI. Possesses hands-on experience in designing and implementing advanced control algorithms for UAVs/USVs, developing real-time computer vision models for edge deployment, and leading multi-agent robotic projects for environmental monitoring. Demonstrated ability to conduct end-to-end research, from simulation and optimization to hardware-in-the-loop testing and field deployment. Have a a strong publication record including conference papers and journal submissions. Proven leadership through founding technical initiatives, managing interdisciplinary teams, and serving as an elected student representative. Seeking to apply expertise in robotics, AI, and embedded systems to innovative R&D or engineering roles in autonomous technology.