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Below is the tentative list of the topics that are available. Please, consider the specified literature as starting point for your literature research.

Topic Area 1: Machine Learning

  1. Computer Vision: Convolutional Neural Networks and Vision Transformers (Daniel Diefenthaler)
  2. Federated Learning (Fabian Dreer)
  3. ML in Computational Sciences and HPC (Sergej Breitner)
  4. AI Sustainability (Karl Führlinger)

Topic Area 2: Generative AI

  1. Generative AI for Text: Transformers (Fabio Genz)
  2. Generative Models for Image Generation (Michelle To)
  3. Multimodel Generative AI (Sophia Grundner-Culemann)
  4. Benchmarking Generative AI (Minh Chung)

Topic Area 3: AI Infrastructure

  1. Data management systems (Sophia Grundner-Culemann)
  2. Vector Databases (Andre Luckow)
  3. Retrieval Augmented Generation (Andre Luckow)
  4. Scaling Machine Learning (Josef Pichlmeier)
  5. AI Hardware (Karl Führlinger)

Topic Area 4: Quantum Computing

  1. Quantum Machine Learning (Florian Kiwit)
  2. Quantum Benchmarking (Florian Krötz)
  3. Quantum Chemistry (Korbinian Staudacher)