Manahil Ahmad

PROFESSIONAL PROFILE Electrical Engineering professional targeting roles in the telecommunications and AI industry, with strong expertise in wireless communication systems (5G/6G), applied AI/ML ,and computer networking. Core experience includes AI-driven optimization of next-generation wireless networks, co-authored an IEEE GLOBECOM 2025 research paper on Deep Reinforcement Learning– based phase shift optimization for stacked intelligent metasurfaces (SIM) in Integrated Sensing and Communication (ISAC) systems. Expert in Machine Learning and Deep Learning, including Supervised Learning, Reinforcement Learning (RL/DRL), Convolutional and Recurrent Neural Networks, Transformers, and Vision Transformers (ViT) . Hands-on experience w i t h Computer Vision, Image Processing, Object Detection (YOLOv8/YOLOS), edge AI deployment, and CUDA programming for GPU acceleration. Possess a solid foundation in computer networks (TCP/IP, SDN, Mininet, virtualization, Linux networking) and wireless system modeling in Python and MATLAB, alongside strong skills in signal processing and communication system analysis. This technical expertise is complemented by proven leadership, project management, and community engagement experience, gained as a UNAI Millennium Fellow and Electrical Team Executive at Formula Student NUST. Through coordinating multidisciplinary teams, managing complex projects, and leading social-impact initiatives, I have developed strong teamwork, communication, and cross-functional collaboration skills, enabling effective contribution to both technical and mission-driven projects in telecom and AI domains. CV Link: https://drive.google.com/file/d/16NaEEtoCYbPSc12toKZuOtUgqYiPOqm4/view?usp=sharing GitHub Link: manahild (Manahil Ahmad) Linkedin: Manahil Ahmad | LinkedIn EDUCATION Electrical Engineering SEECS , Islamabad , 3.16 (2026) INTERNSHIP EXPERIENCE IPT Lab, SEECS, NUST — FYP Intern 17-Apr-2025 - 24-Jan-2026 Conducting research on Stacked Intelligent Metasurfaces (SIM) and Deep Reinforcement Learning (DRL) for next-generation wireless networks (6G), focusing on enhancing data rates, spectrum efficiency, and reliability. Developing a SIM-enabled Integrated Sensing and Communication (ISAC) system model to jointly optimize phase shifts for both communication and sensing functionalities, improving throughput and latency performance in ultra-dense networks. Modeling complex wireless channels and designing learning- based optimization policies to evaluate system-level metrics, including data rate maximization, signal-to-noise ratio, and reliability under realistic propagation conditions. Co-authored IEEE GLOBECOM 2025 paper: “DRL-based Phase Shift Optimization for SIM- enabled Wireless Systems”, demonstrating research impact on 6G system design and optimization. Tools/Skills: Python, PyTorch, MATLAB, Wireless System Modeling, Signal Processing, DRL, ISAC, Simulation. Deep Learning Lab, SINES — Machine Learning Intern 03-Jun-2024 - 12-Sep-2024 Completed specializations in Machine Learning, Deep Learning, Image Processing, and Computer Vision. Implemented various deep learning architectures in CUDA and Python, performing forward propagation for MNIST classification with Multilayer Perceptron (MLP) and verifying results in Keras. Optimized GPU computations using CUDA programming, achieving faster model training and

Electrical Engineering professional targeting roles in the telecommunications and AI industry, with strong expertise in wireless communication systems (5G/6G), applied AI/ML ,and computer networking. Core experience includes AI-driven optimization of next-generation wireless networks, co-authored an IEEE GLOBECOM 2025 research paper on Deep Reinforcement Learning– based phase shift optimization for stacked intelligent metasurfaces (SIM) in Integrated Sensing and Communication (ISAC) systems. Expert in Machine Learning and Deep Learning, including Supervised Learning, Reinforcement Learning (RL/DRL), Convolutional and Recurrent Neural Networks, Transformers, and Vision Transformers (ViT) . Hands-on experience w i t h Computer Vision, Image Processing, Object Detection (YOLOv8/YOLOS), edge AI deployment, and CUDA programming for GPU acceleration. Possess a solid foundation in computer networks (TCP/IP, SDN, Mininet, virtualization, Linux networking) and wireless system modeling in Python and MATLAB, alongside strong skills in signal processing and communication system analysis. This technical expertise is complemented by proven leadership, project management, and community engagement experience, gained as a UNAI Millennium Fellow and Electrical Team Executive at Formula Student NUST. Through coordinating multidisciplinary teams, managing complex projects, and leading social-impact initiatives, I have developed strong teamwork, communication, and cross-functional collaboration skills, enabling effective contribution to both technical and mission-driven projects in telecom and AI domains. CV Link: https://drive.google.com/file/d/16NaEEtoCYbPSc12toKZuOtUgqYiPOqm4/view?usp=sharing GitHub Link: manahild (Manahil Ahmad) Linkedin: Manahil Ahmad | LinkedIn