Batuhan Koyuncu

Batuhan Koyuncu is currently a Ph.D. candidate in Computer Science at Saarland University, affiliated with the ELLIS Ph.D. program and co-advised by Prof. Isabel Valera and Prof. Ole Winther. His research lies at the intersection of deep generative modeling and probabilistic methods for spatial and time-series data. Recently, his work has focused on developing interpretable and scalable architectures for nowcasting and forecasting, with applications in macroeconomics and personalized healthcare. Among his most influential publications is “Variational Mixture of Hyper Generators for Learning Distributions Over Functions” (ICML 2023, with Sanchez-Martin, Peis, Olmos, and Valera), which introduced a flexible generative framework for modeling function distributions. This line of research continues with “Hyper-Transforming Latent Diffusion Models” (ICML 2025, with Peis, Valera, and Frellsen), extending the capabilities of generative models over functions through structured diffusion-based techniques.