I am Uğur Ali Kaplan and currently work as a machine learning engineer at Raynet. In my role, I am responsible for developing and integrating new ML-based solutions with existing products. I also design and build the supporting data and MLOps infrastructure, ensuring scalability and efficiency. Additionally, I actively contribute to discussions with stakeholders, helping to shape the roadmap for ML products and align technical solutions with business objectives.
I hold a degree in computer engineering from Istanbul Technical University, and a master’s degree in machine learning from the University of Tübingen. I completed my master’s thesis at the Bosch Center for Artificial Intelligence.
My academic project portfolio is composed of diverse projects, which include:
- Brain Connectome Prediction with Generative Graph Neural Networks (2020)
- Explainable Treatment Success Prediction in Infertility Clinics (2021)
- Probabilistic and Explainable Forecasting of Air Pollution using Gaussian Processes (2021 – 2023)
- Domain Aware Fine-Tuning of Stable Diffusion for Zero-Shot Domain Adaptation (2024)
Overall, I am passionate about using data-driven approaches to solve real-world problems, and I am constantly seeking new challenges and opportunities to expand my knowledge and skills.