Oral Yalçınpınar

Assisted in 7+ courses as a teaching assistant for C, Java, and Python. Research optimization algorithms for solving NP-Hard problems, with experimental work using quantum computing tools (Qiskit, IBM Quantum).

Built real-time computer vision models using YOLO and TensorFlow. Labeled, trained, and evaluated object detection models on a custom 1,000+ image dataset for anomaly detection, reaching approximately 75% accuracy. Optimized inference on NVIDIA Jetson Orin with CUDA to improve real-time runtime performance. Built end-to-end Python pipelines covering data preparation, training, evaluation, and deployment.

Contributed to Android app development in a team using Java/Kotlin and Git.

Wrote a script to streamline technical documentation, reducing manual reporting effort in a telecom infrastructure environment.

Python, Java, Kotlin, C++, JavaScript.

TensorFlow, PyTorch, Keras, Scikit-learn, YOLO, CNN, OpenCV.

Object Detection, Real-Time Inference, NVIDIA Jetson, CUDA.

Pandas, NumPy, Matplotlib, Seaborn, Feature Engineering.

Git, GitHub, Linux, Docker, Jupyter Notebook, VS Code.

Data Structures & Algorithms, Optimization, Statistics.