Team
PhD Students
Hanna Willkomm
My PhD work is part of the "MemDANCE" project, which aims to develop energy-efficient neuromorphic computing by combining memristor-based hardware with dendritic information processing in neural networks. Within this project, I’m currently inspecting how dendritic properties shape the dynamics, memory, and internal representations of self-organizing recurrent neural networks. The goal is to understand how dendritic processing can enhance robustness and efficiency in neuromorphic systems.
Mahsa Zand
My PhD research explores how interactions unfold over time in complex dynamical systems. Using nonlinear time-series data, I study delayed and directed relationships between system components, especially when these depend on context or shift over time. My work combines dynamical systems theory with machine learning and deep learning to better understand hidden interaction patterns in biological and spreading systems.
Viktoria Zemliak
Tracy Sanchez Pacheco
Hendrik Wilhelm Berkemeyer
Lukas Niehaus
Lukas studied computer science in his bachelor and cognitive science in his master.
In his master thesis "Model-Based Leaf Instance Segmentation on 3D Point Clouds" he applied classical computer vision methods in combination with hyperparameter optimization algorithms to segment individual leaves.
He currently investigates the training behavior of Kolmogorov-Arnold Networks on various initialization strategies.
Laura Krieger
Laura is a PhD student working on predicting the spread of infectious diseases using Bayesian modelling. Her research focuses on how high-resolution spatial data can improve monitoring and forecasting of disease spread, such as during the COVID-19 pandemic. Prior to this project, she was involved in developing the DreamMachine, a low-cost, mobile EEG device, where she focused on software development and signal processing.