Uğur Ali Kaplan Email & Phone Number

Paderborn, North Rhine-Westphalia, Germany

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.

Paderborn, North Rhine-Westphalia, Germany

Renningen, Baden-Württemberg, Germany

I have conducted cutting-edge research exploring the domain adaptation capabilities of latent diffusion models (LDMs) for downstream computer vision tasks, with a focus on semantic segmentation. This work has led to the introduction of novel domain-aware architectural components that actively encourage or discourage using domain cues to improve in-domain.

Tübingen, Baden-Württemberg, Germany

I worked as a research assistant in the “Machine Learning in Sustainable Energy Systems” group at the University of Tübingen under the supervision of Dr. Nicole Ludwig. In collaboration with the Eurasia Institute of Earth Sciences Ocean and Atmospheric Sciences Group and the İTÜ Vision Lab at Istanbul Technical University, I worked on probabilistic air.

Tübingen, Baden-Württemberg, Germany

I assisted with the bachelor-level course ”INF3151 - Introduction to Machine Learning” by grading weekly student assignments and holding practice sessions every week to help students with theoretical and practical exercises.

İstanbul, Türkiye

As an undergraduate research assistant, I worked under the direct supervision of Dr. Gözde Ünal. I had the opportunity to work on industrial collaborations, which gave me firsthand experience working with messy real-world data and using post-hoc explainability techniques. My work formed the basis of my graduation project, titled “Development of Machine.

Istanbul, Turkey

I collaborated with domain experts to perform data organization and cleansing. Additionally, I developed artificial intelligence models for treatment purposes. To interpret the model outputs, I employed interpretability techniques. Furthermore, I deployed the models into production using Ray Serve and created APIs for them. I utilized GoF design patterns.

İstanbul, Turkey

From April to October 2020, I worked as a research intern at Basira Lab under the supervision of Dr. Islem Rekik and graduate student Ahmed Nebli. During my internship, I collaborated with Nebli to develop and train a cascaded graph convolutional network system. This system uses multiple models, where each model takes input from the previous one in a.

Istanbul, Turkey

During my internship, I conducted a comprehensive literature review on General-Purpose Graphics Processing Units (GPGPU). I explored relevant research papers and academic sources to gain a deep understanding of the subject matter. Additionally, I actively participated in weekly project meetings by presenting and discussing papers that offered valuable.

Master Of Science - Ms, Machine Learning, 1.8 (1.0 Is The Best)

Graduation Thesis: Unleashing Text-to-Image Foundation Models for Promptable Domain Adaptation

Bachelor Of Science - Bs, Computer Engineering, 3.69/4.00

Graduation Project: Development of Machine Learning Based Predictive Models for Assistive Reproductive Technology

High School Diploma, Mathematics And Science Track, 95.81/100

* On Full Education Scholarship