Natural and Life Sciences
Helmholtz AI am Helmholtz Zentrum München
Heidi Seibold studied statistics at LMU Munich. In her PhD at the University of Zurich, she developed new machine learning methods for personalised medicine, which are available as open source software. Today, she leads the Open AI in Health working group within Helmholtz AI at the Helmholtz Zentrum München. She is an Knowledge Exchange expert, representative of the German Reproducibility Network, and leads the Open Science Initiative in Medicine of the LMU Open Science Center. She is on the steering committee of the online platform OpenML (Open Machine Learning) and develops open source software. In her research, she combines Artificial Intelligence, Open Science and health research with the goal of making AI and its application in health research transparent, trustworthy and reproducible. Her dream is for research and its components (data, code, etc) to be accessible to all. This could not only improve and fasten the research itself, but in the end also improve or even save human lives.
How can AI be used for health research in a transparent, trustworthy, and reproducible way?