Mine Ögretir

Mine Ögretir is a Doctoral Researcher at Aalto University's School of Science, working within the Department of Computer Science under Harri Lähdesmäki's professorship. Their work focuses on machine learning applications in longitudinal and temporal data analysis.

Mine Ögretir’s research interests lie in Generative Modeling and Temporal Data Analysis, particularly in developing advanced deep learning techniques like variational autoencoders for heterogeneous data structures. Their work bridges computational methods with real-world applications in healthcare and complex data modeling.

Recent publications highlight a consistent focus on machine learning for longitudinal data analysis using variational autoencoders and generative models. Key contributions include methodologies for handling compositional data and heterogeneous temporal datasets, with applications spanning healthcare and biomedical research.

Mine is affiliated with the Lähdesmäki Research Group, contributing to collaborative projects that combine computational innovation with domain-specific challenges. The team’s work emphasizes practical implementations of AI in analyzing complex, time-dependent datasets.