Zu den Inhalten springen

Institute of Medical Biometry and Statistics (IMBI)

Knowledge Discovery and Synthesis

The "Knowledge Discovery and Synthesis" group is investigating methods for identifying potentially complex patterns in data, and methods for synthesizing information from several sources. The spectrum of our work ranges from meta-analysis techniques for clinical trials to machine learning techniques, in particular artificial intelligence/deep learning, for integrating molecular and clinical data.

AG Machine Learning

Kiana Farhadyar

  • Machine Learning (esp. Deep Learning)
  • Distributed Data
  • Deep Generative Models

Maren Hackenberg

  • Machine Learning (esp. Deep Learning)
  • Neural Differential Equations
  • Generative Models

Dr. Moritz Hess

  • Machine Learning (esp. Deep Learning)
  • Feature Learning in High-Dimensional Molecular-Diagnostic Data

Dr. Göran Köber

  • Machine Learning (esp. Deep Learning)
  • Resilience and Vulnerabilty
  • Age-Period-Cohort Analysis

Stefan Lenz

  • Algorithms, (esp. in the Field of Deep Learning)
  • Software Development and API Design

Martin Treppner

  • Deep Generative Models
  • Design of Single Cell RNA-Seq Experiments

Dr. Daniela Zöller

  • Longitudinal Data Modeling
  • Modeling of Clinical Registry Data
  • Modeling of Distributed Data

Dr. Gerta Rücker

  • Meta-Analysis
  • Network Meta-Analysis
  • Meta-Analysis of Diagnostic Accuracy Studies

AG Meta-Analyze

Dr. Sara Balduzzi

  • Meta-Analysis
  • Meta-Analysis of Diagnostic Accuracy Studies

Dr. Guido Schwarzer

  • Meta-Analysis
  • Software Development

AG STRATOS

Federico Bonofiglio

Head

Prof. Dr. Harald Binder

  • Machine Learning (esp. Deep Learning)
  • Integration of Molecular and Clinical Data