Our Research

We use light for computation to bring optical AI into clinical practice. To achieve this, we combine diverse scientific approaches ranging from neuromorphic photonics and nonlinear frequency mixing to programmable fibers and photonic systems.

Neuromorphic Photonics:
We investigate the application potential of intelligent photonic systems that combine programmable optical components with methods from machine learning and nonlinear photonics. The goal is to develop optical learning systems that process data ultra-fast, energy-efficiently, and dynamically, while autonomously responding to their environment or performing complex data analyses directly in the optical domain. Our work is situated at the intersection of physics, data science, and biophotonics.

Nonlinear Frequency Mixing:
We use complex nonlinear wave dynamics, such as supercontinuum generation, to functionalize optical systems. A particular focus lies on neuromorphic, brain-inspired concepts of information processing, where optical wave propagation and its intrinsic nonlinearity are themselves used as computational resources. This enables processing steps to be carried out directly in the optical information space rather than in downstream electronic computing units.

Programmable Fibers and Photonics:
In addition, the Smart Photonics junior research group develops adaptive fiber-based and waveguide-integrated photonic systems that are widely reconfigurable. We design programmable photonic components to enable new imaging and sensing solutions or to serve as analog computing structures. These systems form the basis for intelligent sensors and microscopes that can accelerate and automate diagnostic tasks. With its interdisciplinary approach, the junior research group contributes to the development of autonomous measurement and computing systems, particularly for medical diagnostics, sensing, and energy-efficient information processing.

“My team and I use light waves to study literal flashes of insight.” — Mario Chemnitz