Building intelligent, real-time, AI-driven wireless systems for next-generation networks
π Telecommunication Engineer | AI Specialist | 5G/6G Researcher
Currently pursuing B.Sc. in Telecommunication Engineering at UET Taxila, specializing in:
π‘ Wireless Communication (4G LTE, 5G NR, mmWave)
π€ Deep Learning & Neural Networks
ποΈ Computer Vision & Object Detection
π Reinforcement Learning & Optimization
π Advanced Networking (CCNA β CCIE Path)
β‘ Real-time AI Systems
π― Mission: Architect autonomous, self-optimizing wireless networks powered by AI for the 5G/6G era and beyond.
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Machine Learning & Deep Learning
Computer Vision
Reinforcement Learning
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Wireless Communication
Advanced Networking
Signal Processing
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Revolutionary 5G Resource Management Designed an RL-based dynamic slicing algorithm that intelligently allocates network resources based on user demand, latency requirements, and throughput conditions. Key Achievements:
Tech: Python, Reinforcement Learning, 5G NR, Network Slicing |
AI-Powered mmWave Optimization Developed RL-driven beam selection for mmWave communication systems with dynamic beam steering optimization and enhanced SINR. Key Achievements:
Tech: MATLAB, Python, Reinforcement Learning, Phased Arrays, MIMO |
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Autonomous Navigation System Implemented collision detection model using LiDAR point cloud data for autonomous UAV navigation with real-time obstacle classification. Key Achievements:
Tech: Python, LiDAR, Point Cloud Processing, PyTorch |
Real-Time Computer Vision Application Built real-time YOLOv8 detection system with screen capture, model inference, and Arduino-triggered precision actions. Key Achievements:
Tech: YOLOv8, OpenCV, Arduino, Python, Real-time Processing |
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Complete Wireless Communication Chain Developed full OFDM transceiver with modulation, IFFT/FFT, cyclic prefix, channel modeling, and BER analysis. Key Achievements:
Tech: MATLAB, OFDM, QPSK/16-QAM, Digital Communication |
RL-Based Adaptive Traffic Control Implemented Q-Learning traffic light system with dynamic timing adjustments and multi-intersection coordination. Key Achievements:
Tech: Python, Q-Learning, Reinforcement Learning, Simulation |
| Project | Description | Tech Stack |
|---|---|---|
| π LiDAR-Camera Fusion | Multi-modal sensor fusion for enhanced perception | Python, OpenCV, Point Cloud |
| π€οΈ Obstacle Avoidance UAV | 2D simulation with RL-powered navigation | Python, Reinforcement Learning |
| βΎ MLB Score Predictor | Machine learning for baseball forecasting | Python, Scikit-learn, Pandas |
| ποΈ Huffman Compression | Lossless data compression algorithm | C++, Data Structures |
| π Advanced Network Labs | OSPF, BGP, VLAN configurations | Cisco Packet Tracer, GNS3 |
| π‘ Antenna Simulations | Radiation patterns & propagation models | ANSYS HFSS, MATLAB |
| π¦ Traffic Sign Detection | Real-time road sign classification | YOLO, OpenCV, Python |
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University of Engineering & Technology (UET) Taxila, Pakistan Specialization Areas:
Cadet College Skardu | Higher Secondary (Classes 8-12) |
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Network Optimization
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5G/6G Technologies
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UAV & Robotics
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timeline
title Career & Learning Journey
2024 : CCNA Certified
: 5G NR Fundamentals
: ML Project Portfolio
2025 : CCNP Enterprise
: Research Publications
: 6G Prototype Systems
2026 : CCIE Preparation
: Industry Leadership
: Open Source Contributions
2027+ : 6G Architecture
: Global Innovation
: Research Excellence
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β
Mastering 5G NR Architecture |
π― Complete CCNP Enterprise |
π« CCIE Certification |
I'm actively seeking collaboration opportunities in:
π¬ Have an interesting project or research idea? Let's connect!

