Prof. Dr. med. Dr. phil. Andras Jakab

Area of Research

Development/Developmental Biology Imaging Neuro Sciences Radiology/Nuclear Medicine Artificial Intelligence Machine Learning

Description of Research Interest

I am interested in how the human brain develops under normal and pathological conditions. With my research group, we are exploring novel ways to understand how long-term cognitive development of children is affected by early brain maturation.

My team uses the latest computational imaging, image analysis and machine-learning methods, ranging from neonatal and fetal MRI segmentation, structural and functional connectomics, and quantitative mapping of brain development to generative AI approaches for data augmentation, digital twins and advanced diagnostic modelling. We develop techniques that will catalyse research as part of a multidisciplinary network in prenatal diagnostics and surgery, neonatology, pediatric cardiology, neurodevelopment and child health in Zürich. Our work spans large-scale clinical studies, international collaborations and translational applications aimed at improving early detection and long-term outcomes for vulnerable patient populations.

Special Expertise


  • Fetal and infant MRI acquisition and analysis
  • Computational image analysis: image generation, segmentation, growth quantification
  • Neural connectivity studies: animal models, MRI based connectivity mapping, connectomics and graph theory
  • Clinical outcome research, multivariate statistics
  • Organizing open science projects and conference workshops, challenges
  • Advanced pediatric neurosurgical planning using connectomic mapping and patient-specific 3D visualizations
  • Academic leadership, supervision of early stage researchers and leading international collaborations

Shareable Platforms, Services, Equipment & Infrastructure


  • Fetal and developmental MRI data of normal and pathological development
  • In-house developed atlases of the human fetal and neonatal brain
  • Specialized image generation and segmentation methods, machine-learning networks
  • 3.0T MRI for pediatric imaging (including fetal), contact: Center for MR-Research, University Children's Hospital Zürich

Member of Collaborative/interdisciplinary Research Consortia


  • URPP AdaBD
  • LOOP BMIP2
  • ZNZ (Zurich Neuroscience Center) member

all professors
Prof. Dr. med. Dr. phil. Andras Jakab
University of Zurich Faculty of Medicine
University Children's Hospital Zurich
Fetal and Infant Developmental Imaging
andras.jakab@kispi.uzh.ch www.kispi.uzh.ch