StuWS: Tech of the brain – from neuromonitoring to AI and ethics

The human brain remains one of the most complex and least understood organ systems in medicine. As direct monitoring is limited, our understanding of brain function largely relies on non-invasive signals. Techniques such as near-infrared spectroscopy, electroencephalography, pupillometry, and electrocardiography provide complementary insights into cerebral oxygenation, neuronal activity, and brain–heart interactions.

Combining these time-synchronized data streams—referred to as multimodal neuromonitoring—offers the opportunity to gain a more comprehensive understanding of brain function than any single modality alone. At the same time, such high-dimensional data exceed the capacity of traditional analytical approaches. Machine learning enables the integration of heterogeneous data, opening new possibilities for understanding brain function.

In this 3-day interdisciplinary workshop, participants will explore the key question:
What meaningful information about brain function can be inferred from multimodal, non-invasive neuromonitoring data?

Senior Fellows:

• Prof. Raimund Helbok, PhD, MD, Department of Neurology & Clinical Research Institute for Neuroscience, Kepler University Hospital, Johannes Kepler University, Linz
• Ass. Prof. Erich Kobler, PhD, Institute for Machine Learning, Johannes Kepler University, Linz
• Ethan Moyer, Moberg Analytics Inc
• Jeanette Tas, PhD, Department of Neurology, Kepler University Hospital, Johannes Kepler University,  Linz
• Prof. Gernot Müller-Putz, PhD, Institute of Neural Engineering, Graz University of Technology
• Reinmar Kobler, PhD, Meta Reality Labs

Workshop content:

• Hands-on experience with neuromonitoring devices
• Design of experimental measurement protocols
• Development of AI-based strategies for data analysis
• Insights into neuromonitoring in neurocritical care
• Discussion of ethical aspects of AI in neuroscience

The workshop bridges human brain physiology and data science, equipping early-career researchers with both methodological and critical skills.

Target group:
PhD students and postdoctoral researchers from diverse disciplinary backgrounds with an interest in neuroscience, medicine, data analysis, and AI.
To apply for the workshop, candidates are required to submit a motivation letter outlining their interest in the topic and their expectations for participation.