Daniel M. Lang

Daniel M. Lang

Research Scientist

Helmholtz Center Munich

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.

Interests
  • dynamic imaging
  • generative modeling
  • self-supervised learning
Education
  • PhD in Physics, 2022

    Helmholtz Munich and Technical University Munich

  • MSc in Physics, 2018

    University Regensburg

  • BSc in Physics, 2016

    University Regensburg

Teaching
  • Self-supervised Learning in Medical Imaging - Theory and Applications (IN2107, IN45089)

    Master seminar | WS23/24 |

  • Interpretable AI in Medical Imaging (IN2107, IN45009)

    Master seminar | SS23 |

Student Projects & Theses
  • Diffusion-Based Correspondences between Multimodal Medical Images

    IDP | 2025 | Xingju Zhang | ongoing |

  • Unsupervised Temporal Diffusion-Based Interpolation for 4D CT

    Master's Thesis | 2025 | Zeyad Mahmoud | finished |

  • Text Conditioned Brain MRI Editing

    IDP | 2025 | Demir Arikan | finished |

  • Diffusion Models for Counterfactual Pathology Synthesis

    Master's Thesis | 2024 | Malek Ben Alaya | finished |

  • Identification of Radiotherapy-Induced Lung Damage on Dark Field Imaging Data

    Master's Thesis | 2024 | Anna-Maria Weber | finished |

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