Projects
Research Topics:
Frameworks
- Conditional Diffusion Evolution: a deep-learning baed approach to use iteratively refined diffusion models to generate high-quality, well adapted offspring in an ongoing evolutionary search. Classifier-free guidance techniques allow guiding the generative denoising towards solutions with target traits via conditional sampling in parameter space, for phenotypical traits, and population-wide features.
- Diffusion Evolution: a model-free approach of using diffusion models as evolutionary algorithm, allowing for leveraging advancements in diffusion models for evolutionary algorithm tasks, including accelerated sampling and latent space diffusion.
- mindcraft: a modular reinforcement learning framework for robust and interpretable autonomous navigation
- bio-feedback: a framework to synchronously gather, process, and control bio-sensory data
- data-monitor: an interactive (non-blocking)
matplotlib-based time-series visualization tool
- gempy:
Python implementations of different generative models (maximum entropy method -
NumPy & Numba, Variational-Autoencoder - PyTorch)
- cthru: a software to minimize reflection in video data of an optical multi-polarization filter system
- atuin: a Python-based framework for evolutionary optimization of nested data structures - developed during my Ph.D. (available on demand)
Coding Challenges
Applications and Hobby
- Inkstrument: an AI-based music controller (WIP)
- Raspberry Pi brewery (putting CraftBeerPi by Manuel Fritsch to use)