We work on advancing AI algorithms and solutions to tackle complex discrete planning and scheduling optimization problems. Our research comprises:

  • methods to facilitate the modeling of such problems using patterns,
  • new algorithmic solutions for the representation of huge data instances, originating for example from bioinformatics,
  • systematic classifications of application classes such as traveling sales person problems,
  • applications of reinforcement learning to scheduling problems with many dead-end states,
  • AI project management methods,
  • AI reference architectures and architectural decision making in AI solution architectures.


Office Administration:

Andrea Nawrath-Herz


Postdoctoral Researcher:

Dr. Sophia Saller


Scientific Staff/PhD Students:

Alexis Bernhard
Annika Engel
Katharina Hengel
Wenhao Lu


Student Assistants:

Anastasia Salyaeva
Anna Kenter
Alisa Welter
Eva Röper