Our research focus is on the application and development of artificial intelligence (AI) tools, such as deep neural networks, in the field of communication disorders. We foster new image acquisition and image processing techniques and work on TinyML neural networks. We further develop new datasets together with our clinical collaborators and work on the quantification of health states. As most of our work is clinically motivated, we seek solutions that have an impact on diagnosing, treating, and monitoring patients. Please see also our publications.

Knowledge Domains

Embedded AI

We are optimizing AI algorithms to fit on constrained computing devices, such as microcontrollers and Edge TPUs. For example, we use evolutionary algorithms with custom objective functions to propose the best deep neural network architecture for a given environment.

Computer Vision

We are experts in deriving a pixel-wise classification in a given image (semantic segmentation) with a focus, but not limited to, biomedical images. We further use object detection and (markerless) tracking algorithms to compute animal or object trajectories. With this, we are able to uncover behavioral phenotypes of animals, cancer phenotypes or single-cell neural activity patterns. We create custom interfaces to efficiently label and annotate (biomedical) data.

XD biomedical signal analysis

We work on multidimensional (XD) data, such as audio (1D), images (2D), videos or z-stacks (3D), as well as time-lapse imaging (4D).

Image acquisition techniques

We have experience in designing, building, operating, and evaluating microscopes, such as DMD-based, light-sheet, and two-photon microscopes, as well as custom behavioral rigs and endoscopy systems. We not only combine and create novel hardware components but also provide graphical user interfaces (GUIs) to interact with our tailored systems.

Industry collaborations

Please get directly in touch with us.

Open projects

If you are interested in an internship, or a Bachelor’s or Master’s thesis project in our lab, please get in touch with Likewise, if you have a project that you think fits the lab’s scope, please feel free to contact us. We recommend a strong background in Python programming, Pattern Recognition, and Deep Learning (at least familiar with either TensorFlow, PyTorch, or Jax/Flax), and signal/image processing. All projects are designed such that they are research-oriented and may yield a scientific publication. Here are the open projects in the lab that can be tackled (e.g. winter term 2023/2024) – we are full in SS 2023:

  • Beyond Dice and IoU: Development and Evaluation of a Novel Semantic Segmentation Loss
  • Efficient image processing on Edge TPUs
  • Deep Learning in the web browser – using TensorFlow.JS for time-variant image inference
  • Normalization in Deep Neural Networks – a systematic analysis
  • Mechano-acoustic digital biomarkers
  • Generative Deep Learning applied to endoscopic Images
  • Biomedical NeRF (Neural Radiance Fields, previous background required)
  • Diffusion models for biomedical image segmentation


We are grateful to receive generous funding from

  • Bundesministerium für Bildung und Forschung (BMBF)
  • Staatsministerium für Wissenschaft und Kunst, Bayern (StMWK)
  • Bayerische Forschungsallianz (BayFOR)
  • Joachim-Herz-Stiftung
  • Innovationsfonds Lehre
  • KI Campus des Stifterverbands
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