I build production-minded machine learning systems, real-time computer vision applications, and practical AI products.
I am a Computer Engineering student at Pamukkale University, focused on turning machine learning research into reliable, usable systems. My work spans object detection and tracking, visual perception pipelines, data-driven APIs, and LLM-based agent workflows.
- Building real-time computer vision and applied ML systems with Python.
- Interested in model integration, inference pipelines, data analysis, and measurable product outcomes.
- Open to internships, early-career opportunities, and technical collaborations.
| Area | Technologies |
|---|---|
| Machine Learning | PyTorch TensorFlow scikit-learn Keras |
| Computer Vision | OpenCV YOLO DeepSORT Tesseract OCR |
| Data | Pandas NumPy SQL PostgreSQL MySQL |
| Engineering | Python Flask REST APIs Docker GitHub Actions |
| Project | What it does | Stack |
|---|---|---|
| Lane Violation Detection | Detects and tracks vehicles, identifies lane violations, and supports review workflows through desktop and web interfaces. | Python YOLO DeepSORT OpenCV PyQt Flask |
| SmartVision | Provides real-time object detection and spoken guidance designed to assist visually impaired users. | Python YOLOv8 OpenCV TTS |
| LLM Multi-Agent Retail Optimization | Coordinates demand forecasting, inventory management, and pricing workflows through an LLM-based multi-agent system. | Python LLMs LangChain Google ADK |
Software Engineering Intern, Kodpit | Jun 2025 to Aug 2025
Built an end-to-end lane detection and vehicle tracking pipeline with Python and OpenCV, using a modular architecture designed for deep learning model integration.
B.Sc. Computer Engineering, Pamukkale University | 2021 to Present
Concentrating on data-driven AI, computer vision, and practical machine learning systems.
I am open to internships, ML/CV engineering opportunities, and collaborations on useful AI products. The best way to reach me is at firatyavas12@gmail.com.