Dr. Antonios G. Dougalis is a neuroscientist and neurophysiologist whose research combines cellular neurophysiology, electrophysiology, computational neuroscience, signal analysis, and machine learning to investigate brain dynamics in health and disease. He received his Ph.D. in Cellular Neurophysiology and Neuropharmacology from the University of Sunderland, United Kingdom, in 2005 and has held research positions at several international institutions, including Imperial College London, the University of Manchester, the University of Ulm, Dublin City University, and the University of Eastern Finland, where he formerly led the Laboratory for Human Cellular and Network Neurophysiology. His research focuses on understanding how alterations in neuronal and microcircuit physiology become expressed at the level of large-scale brain dynamics. Current interests include electrophysiological biomarkers, neural connectivity, critical dynamics, multiscale brain organization, and physiologically interpretable machine learning approaches for neurodegenerative disorders. More broadly, his work aims to bridge cellular neurophysiology, systems neuroscience, and applied mathematics to understand how brain states emerge, evolve, and transition across multiple spatial and temporal scales.