Daniel Lang is a postdoctoral researcher at the Institute of Machine Learning in Biomedical Imaging at Helmholtz Munich. Additionally, he holds the role of a principal investigator in the Helmholtz Imaging Project CLARITY, and is a fellow of the Helmholtz HPP postdoc program.

His research primarily focuses on the development of machine learning models for dynamic imaging, with a specific emphasis on applications in cancer diagnosis and treatment. Daniel’s key areas of interest include but are not limited to: generative modeling, synthetic image generation, self-supervised learning, transfer-learning, and domain adaptation.