GenAI - Generative Models


GenAI Research group is founded with main focus on generative models used for different downstream tasks such as scene generation and manipulation, multi-modal data generation, and representation learning. The research done by GenAI includes (but is not limited to) image generation and manipulation, scene graphs, semi, weakly, and self-supervised learning, meta-leaning, and federated learning. The group also organizes the Deep Learning for Medical Applications (DLMA) seminar and the Machine Learning in Medical Imaging (MLMI) practical course.

Contact Person / Group Coordination

Azade Farshad -

Research Partners

Munich Center for Machine Learning (MCML)
Stanford University
Ludwig Maximilian University 
Klinikum Recht Der Isar
Imperial College London 
NVIDIA healthcare 
FAU Erlangen University
Oxford University
Helmholtz AI 
Johns Hopkins 
Harvard Medical School
Sharif University

Group Members


  • Peter Weinberger
  • Anastasia Makarevich
  • Sabrina Musatian
  • Sarthak Garg
  • Samin Hamidi
  • Maximilian Frantzen
  • Onat Sahin
  • Sraddha Das
  • Pavel Jahoda
  • Mahaut Gerard


  • MLMI
  • DLMA


Campus Garching

Chair for Computer-Aided Medical Procedures and Augmented Reality,
Boltzmannstr. 3, 85748 Garching b. Munchen