معرفی
David Källberg is an Associate Professor at the School of Business, Economics and Statistics (USBE), Umeå University, specializing in Statistics. His research focuses on statistical methods for high-dimensional data analysis, entropy estimation, and mixture modeling.
Research Interests: David's work bridges statistical theory and practical applications in genomics and machine learning. Key areas include:
- Entropy balancing for causal effect estimation
- Feature selection in high-dimensional clustering (e.g., RNA-seq data)
- Mixture models for biomedical applications
- Nonparametric methods for entropy-type functionals
- Image matching algorithms in large databases
- Integration of epigenetic and clinicopathological data
Collaborations: He collaborates with researchers like Patrik Rydén, Linda Vidman, and Ingeborg Waernbaum, contributing to journals such as Frontiers in Genetics, PLOS ONE, and Lecture Notes in Computer Science. He is also a member of the Stat4Reg research group.
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