Robotics and Intelligent Systems Engineering Student Department of Robotics and Intelligent Systems Engineering, Manara University, Syria

I am a robotics & AI engineering student and researcher specializing in autonomous systems, computer vision, and machine learning applications. My research interests encompass simultaneous localization and mapping (SLAM), path planning algorithms, object detection systems, and remote sensing applications. Currently affiliated with the Department of Robotics and Intelligent Systems Engineering at Manara University and contributing to research initiatives at DualMind-Lab, I focus on developing robust, real-world solutions that bridge theoretical frameworks with practical implementations.

My work emphasizes the integration of classical robotics principles with modern machine learning techniques, particularly in resource-constrained environments. I am committed to advancing the field through rigorous research, open-source contributions, and the mentorship of emerging roboticists through competitive platforms such as the World Robot Olympiad (WRO).

• SLAM & Localization: Multi-sensor fusion, QR-based localization, real-time mapping
• Path Planning: Global and local planners, obstacle avoidance, behavior tree architectures
• Sensor Processing: LIDAR data processing, sensor fusion algorithms
• Robot Kinematics & Dynamics: Forward/inverse kinematics, differential drive systems, serial manipulators
• Real-Time Systems: Embedded control, real-time navigation architectures

• Object Detection: YOLOv8 implementation, custom model training, waste classification systems
• Image Processing: Classical computer vision algorithms, feature extraction, image enhancement
• Deep Learning Frameworks: PyTorch, PyTorch Lightning, transfer learning methodologies
• Vision-Based Systems: Visual localization, QR code detection and processing

• Supervised Learning: Regression, classification, ensemble methods
• Advanced ML Algorithms: TabPFN, XGBoost, LightGBM, Support Vector Machines
• Model Optimization: Hyperparameter tuning, cross-validation, performance evaluation
• Data Engineering: Feature engineering, data preprocessing, statistical analysis
• Large-Scale Datasets: Handling and processing multi-dimensional datasets

• Satellite Imagery Processing: Sentinel-2 data analysis, multispectral image processing
• Change Detection: Temporal analysis, anomaly detection in satellite imagery
• Atmospheric Data Analysis: Aerosol analysis, environmental monitoring
• Geospatial Feature Extraction: Spectral indices, texture analysis, spatial statistics

• Languages: Python, C++, MATLAB, CUDA, C, Shell scripting
• Robotics Frameworks: ROS (Robot Operating System), Arduino
• Deep Learning: PyTorch, TensorFlow, YOLOv8, PyTorch Lightning
• Development Tools: Git, Linux, GPU programming, CMAKE
• Simulation: MATLAB/Simulink, Webots, Gazebo

Comprehensive implementation of autonomous robot navigation algorithms encompassing the complete pipeline from SLAM to local planning.

Technologies: Python, C++, CUDA, Makefile Key Contributions:

• Implemented multiple path planning algorithms including A*, RRT, and hybrid approaches
• Developed behavior tree-based control architecture for adaptive decision-making
• Integrated GPU acceleration (CUDA) for computational efficiency in real-time applications
• Created modular framework supporting both simulated and real-world deployment

Skills Demonstrated: SLAM, path planning, behavior trees, GPU programming, autonomous navigation

Advanced navigation system combining visual localization with LIDAR-based obstacle detection for robust autonomous operation.

Technologies: Python, C++, C, Shell Key Contributions:

• Developed QR code-based localization system for global positioning
• Implemented real-time LIDAR processing for dynamic obstacle mapping
• Created sensor fusion algorithm integrating visual and range data
• Designed low-latency navigation stack suitable for embedded systems

Skills Demonstrated: Real-time systems, sensor fusion, QR code processing, LIDAR mapping, obstacle avoidance

Technical lead for RoboPegasus team competing in the World Robot Olympiad Future Engineers category.

Technologies: C++, Python, Arduino Technical Highlights:

• Designed autonomous vehicle navigation system
• Implemented embedded control algorithms
• Developed robust sensor processing pipeline for competition environment

National competition submission showcasing autonomous vehicle capabilities for the WRO Future Engineers challenge.

Technologies: C++, Python Technical Highlights:

• Autonomous navigation in constrained environments
• Real-time obstacle detection and avoidance
• Embedded systems programming for robotics applications

Coaching Record: As a robotics coach at Manara University, mentored teams achieving 5th place (Year 1) and 3rd place (Year 2) in National WRO competitions.

• Manara University - Department of Robotics and Intelligent Systems Engineering
• DualMind-Lab - Research Organization focusing on machine learning and computer vision applications

My current research focuses on:

• Autonomous Systems: Developing robust navigation and planning algorithms for real-world deployment
• Computer Vision: Advancing object detection and image analysis techniques
• Machine Learning Applications: Exploring data-efficient learning methods and transfer learning
• Remote Sensing: Investigating satellite imagery analysis for environmental monitoring
• Robotics Education: Enhancing pedagogical approaches for robotics and AI instruction

I am open to collaborations in robotics research, particularly in:

• Autonomous navigation systems
• Computer vision applications
• Machine learning for robotics
• Educational robotics initiatives

Email: lazkani.baraa.official@gmail.com GitHub: @BaraaLazkani Resume Resume