Muhammad Abu Baker

PROFESSIONAL PROFILE Electrical Engineering graduate with 1.5+ years of research experience in 6G wireless communication, including channel modeling, data-rate optimization, and intelligent metasurfaces. Strong expertise in deep reinforcement learning for adaptive and environment- aware wireless systems, with hands-on experience in agent interaction, reward design, and performance optimization. Background in embedded system design and chip-level programming, with practical exposure to camera-based computer vision, image acquisition pipelines, and core visual processing algorithms. EDUCATION Electrical Engineering School of Electrical Engineering and Computer Sciences , Islamabad , 3.14 (2026) INTERNSHIP EXPERIENCE Information Processing and Transmission (IPT) Lab 31-Mar-2025 - 22-May-2026 Researched 6G network architectures using analytical and simulation approaches, focusing on data-rate optimization, interference management, and intelligent mobile network control using deep reinforcement learning. System on Chip (SoC) Lab 01-Jul-2024 - 31-Aug-2024 Designed and implemented digital logic circuits on DE-series FPGA boards using Verilog, gaining hands-on experience with FPGA tools, HDLs, circuit testing, and optimized digital system integration. Optical Networks and Technologies (ONT) Lab 01-Jun-2025 - 31-Aug-2025 Worked with O-RAN architecture and generated GAN-based RF IQ datasets to train RAN Intelligent Controllers, improving robustness of AI-driven RAN optimization through data augmentation using OTA and emulation methods. FINAL YEAR PROJECT Intelligent Control of SIM-Assisted Wireless Networks Using Deep Reinforcement Learning. Developed a deep reinforcement learning–based control framework for SIM-assisted wireless networks, optimizing metasurface configurations to enhance sum-rate, spectral efficiency, and adaptive signal propagation under dynamic channel conditions for next- generation communication systems. TECHNICAL EXPERTISE Language Python, C++/C, Java, MATLAB, Verilog API and Libraries Pandas, Numpy, Scikit-learn, Pytorch, Tensorflow, OpenCV Design and Simulation Tools

Electrical Engineering graduate with 1.5+ years of research experience in 6G wireless communication, including channel modeling, data-rate optimization, and intelligent metasurfaces. Strong expertise in deep reinforcement learning for adaptive and environment- aware wireless systems, with hands-on experience in agent interaction, reward design, and performance optimization. Background in embedded system design and chip-level programming, with practical exposure to camera-based computer vision, image acquisition pipelines, and core visual processing algorithms.