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oguzhan-gun/README.md

Oğuzhan Gün

Computer Engineer focused on Autonomous Systems, AI, Robotics, and Computer Vision.

Featured Projects

🤖 LLM-Powered ERP Analytics System RAG, Multi-Agent Systems, NL-to-SQL, Vector Search

🚁 Autonomous Combat UAV ROS2, Gazebo, PX4, MAVLink, YOLO, Kalman Filtering, Sensor Fusion

⚽ RoboKeeper Stereo Vision, Trajectory Prediction, Robotics

🥊 MMA-AI CNN-LSTM, XGBoost, Computer Vision

Technologies

AI/ML: PyTorch • TensorFlow • Transformers • OpenCV • YOLO • MediaPipe • XGBoost

Robotics: ROS2 • Gazebo • PX4 • ArduPilot • MAVLink

Programming & Tools: Python • C++ • SQL • PostgreSQL • Linux • Git

Research Interests

Reinforcement Learning • Embodied AI • Multi-Agent Systems

Contact

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  1. LLM-Powered-LOGO-ERP-Analytics-System LLM-Powered-LOGO-ERP-Analytics-System Public

    LLM-powered ERP analytics platform with NL2SQL, RAG, and multi-agent reasoning.

    Python 1

  2. autonomous-uav autonomous-uav Public

    Autonomous air-to-air combat UAV system featuring predictive guidance, sensor fusion, and real-time target tracking using ROS 2, PX4, and YOLOv11.

  3. robokeeper-stereo-vision robokeeper-stereo-vision Public

    Real-time stereo vision and physics-based soccer ball trajectory prediction for robotic goalkeeper systems using C++, ROS 2, and Gazebo.

  4. mma-finish-prediction-cnn-lstm mma-finish-prediction-cnn-lstm Public

    Deep learning model that predicts UFC fight finish methods (KO/TKO, Submission, Decision) using a hybrid CNN-LSTM architecture.

    Python

  5. mma-finish-prediction mma-finish-prediction Public

    Ensemble XGBoost system for predicting MMA fight winners using fighter statistics and feature engineering.

    Python