Muhammad Umer Haroon

PROFESSIONAL PROFILE I am an ambitious final year Electrical Engineering student at NUST with a strong background in Computer Vision, AI, robotics systems, and digital/embedded design. I have worked on a range of academic and internship projects including vision-based pipelines, machine learning models, and a ROS2-based autonomous robotic system for my Final Year Project. I have a solid foundation in circuit design, microcontrollers, and system-level engineering, and I enjoy combining software, algorithms, and hardware concepts to build practical, real-world systems. I bring strong problem-solving, teamwork, and leadership skills, with experience in technical documentation, project coordination, and delivering complex systems under academic deadlines. EDUCATION Electrical Engineering SEECS , Islamabad , 3.15 (2026) INTERNSHIP EXPERIENCE Systems Limited 10-Jun-2025 - 07-Aug-2025 During my AI/Data Science internship, I worked extensively on data preprocessing, cleaning, and exploratory data analysis (EDA) using Python, Pandas, NumPy, Matplotlib, and Seaborn. I developed and evaluated machine learning models for classification tasks and worked with real-world datasets from Kaggle and other sources. I fine-tuned BERT-based models for NLP tasks including spam classification and named entity recognition, and implemented model evaluation and explainability using techniques such as SHAP and LIME. I also worked with sentence embeddings (SBERT) for semantic similarity and clustering, gaining hands-on experience in building end-to-end data-driven and AI pipelines using Jupyter Notebook and VS Code. FINAL YEAR PROJECT Lidar-Guided Rover for Landmine Detection My Final Year Project is a ROS2-based LiDAR-guided autonomous ground rover designed for navigation in hazardous and disaster affected environments. The system integrates 2D LiDAR, SLAM, the Nav2 navigation stack, costmaps, and path planning to perform autonomous mapping, localization, and obstacle avoidance in unknown environments. The rover is developed and tested in Gazebo and visualized in RViz using a modular perception and navigation architecture that supports future sensor integration, including metal detectors and thermal cameras for landmine detection and human presence detection. The project emphasizes safe and reliable autonomous navigation, scalable system design, and real world applicability in high risk areas. TECHNICAL EXPERTISE Computer Vision & Image Processing: OpenCV, Feature Matching, Optical Flow, Homography Experience building vision pipelines for motion analysis, object tracking, feature extraction, and geometric transformations using Python and OpenCV. Machine Learning & Deep Learning: scikit-learn, PyTorch, HuggingFace Transformers Experience in training, fine-tuning, and evaluating machine learning and deep learning models for classification and NLP tasks using real-world datasets. Robotics & Autonomous Systems: ROS2, SLAM, Nav2, Gazebo, RViz Experience developing and simulating autonomous navigation systems using LiDAR-based SLAM, path planning, localization, and

I am an ambitious final year Electrical Engineering student at NUST with a strong background in Computer Vision, AI, robotics systems, and digital/embedded design. I have worked on a range of academic and internship projects including vision-based pipelines, machine learning models, and a ROS2-based autonomous robotic system for my Final Year Project. I have a solid foundation in circuit design, microcontrollers, and system-level engineering, and I enjoy combining software, algorithms, and hardware concepts to build practical, real-world systems. I bring strong problem-solving, teamwork, and leadership skills, with experience in technical documentation, project coordination, and delivering complex systems under academic deadlines.