Our research group aims to bring tools and methods from computer science, nonlinear dynamics to applied sciences.
Seizure Dynamics
Epilepsy is a chronic brain disorder that affects about 1% of the population. It is characterized by the onset of excessive synchronized neuronal activity. In this research topic we aim at developing frameworks to predict and detect the onset of seizures using machine learning along with data and simulations. How are seizures are triggered? How can they be stopped? Can factors like temperature or stress facilitate the onset of seizures?
Check out our most recent paper on the topic: https://doi.org/10.1063/5.0219836
Brain Simulations
The brain is a complex system with billions of cells called neurons that are responsible for keeping us alive. In this research theme we aim to develop computational models to help understand the intricacies of the brain. How do neurons interact with each other? How does temperature affect their behavior? How is information processed? What are the fundamentals of memory formation?
Predictions with Machine Learning
Machine learning is a segment of artificial intelligence that uses data for learning and performing tasks without knowledge of the mechanisms behind that task. Applications of machine learning have become widespread, permeating our day-to-day lives through many services we use, sometimes not even realizing that certain jobs are being performed by a machine. In this research theme we aim to add scientific knowledge to the data driven training process in machine learning for improving the machine’s prediction capability.