Hamid Karimi-Rouzbahani

Dr. Hamid Karimi-Rouzbahani is a Research Fellow and ARC DECRA Fellow at the Queensland Brain Institute, Faculty of Health, Medicine and Behavioural Sciences, The University of Queensland. He previously held a Newton Fellowship at the MRC Cognition and Brain Sciences Unit, University of Cambridge, highlighting his international research experience.

His research lies at the intersection of Computational, Cognitive, and Clinical Neuroscience, integrating neural signal processing (EEG, MEG, fMRI), machine learning (deep neural networks), and mathematical modelling. He develops advanced methods for multidimensional connectivity and decoding analysis to understand information coding and transfer in the brain. His cognitive research focuses on visual perception, attention, and the multiple-demand system, while his clinical work aims to quantify and localize brain areas involved in epilepsy.

The analysis of his recent publications reveals a strong trend in developing and applying computational models to both fundamental cognitive processes and clinical applications, particularly in epilepsy. His work consistently bridges methodological innovation with empirical neuroscience, using multimodal data to extract meaningful neural signatures.

Scientific Awards:

• ARC DECRA Fellow (Discovery Early Career Researcher Award)
• Newton Fellowship, MRC Cognition and Brain Sciences Unit, University of Cambridge

Dr. Karimi-Rouzbahani is actively involved in research supervision, currently serving as the Principal Advisor for a PhD project on developing novel information decoding and tracking methods. He is the lead investigator on an ARC-funded project (2023–2029) titled "Characterising brain networks of intelligence through information tracking," which demonstrates his success in securing competitive research grants. He is available for supervision and collaborates with researchers across various institutions.

His work is conducted within the Queensland Brain Institute, a world-leading neuroscience research centre, where he contributes to collaborative projects like #EEGManyLabs, emphasizing reproducibility in EEG research.