Uğur Kaplan is a Machine Learning Engineer with nine years of experience building ML products, research prototypes and scalable MLOps infrastructure across industry and academia. He blends hands-on deployment skills (Ray Serve, APIs, testing) with cutting-edge research in computer vision and diffusion models, notably exploring domain-aware LDM components and cross-attention prompting for improved segmentation and cross-domain adaptation. His background spans healthcare, atmospheric sciences and energy forecasting, where he has delivered probabilistic models and productionized AI systems informed by domain experts. Based in Paderborn, Germany, he moves fluidly between stakeholder-facing roadmap work and low-level model engineering, and his master’s research at BCAI highlights an unusual focus on steering diffusion models to selectively use domain cues.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Computer Engineering, 3.69/4.00, Bachelor of Science - BS, Computer Engineering, 3.69/4.00 at İstanbul Teknik Üniversitesi
Master of Science - MS, Machine Learning, 1.8 (1.0 is the best), Master of Science - MS, Machine Learning, 1.8 (1.0 is the best) at Eberhard Karls Universität Tübingen
High School Diploma, Mathematics and Science Track, 95.81/100, High School Diploma, Mathematics and Science Track, 95.81/100 at TED Mersin High School
Insertion Sort, Quick Sort, Merge Sort, Min Heap, Priority Queue, Red Black Tree, Order Statistic Tree, Graph Creation, Breadth-First and Depth-First Search and Homework Assignments
Contributions:26 commits, 1 PR, 13 pushes in 11 months
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