Sergio Mora Camargo is an Engineering Ph.D. student at Tecnológico de Monterrey, Mexico, with an interdisciplinary background in neuroscience, acoustics, audiology, and engineering. He holds a B.S. in Music and Sound Engineering (2019) and an M.Sc. in Engineering (2021) from Tecnológico de Monterrey. His research focuses on acoustic neuroengineering, computational audiology, auditory processing, and auditory gamification, with particular interest in auditory discrimination training, neuroaudiological assessment, and audio and biosignal processing. His work explores the intersection of clinical audiology, neuroscience, and technology to better understand and enhance auditory abilities. Sergio has presented his work at academic conferences and scientific events in Mexico, Brazil, the United States, and Spain, addressing topics including the neurological mechanisms of tinnitus, the effects of noise on health, and gamification in auditory discrimination. He has also gained clinical experience through rotations at Zambrano-Hellion Hospital and the Mexican Institute of Otology and Neurotology, where he worked with audiological assessments, auditory evoked potentials, and hearing-device measurement and calibration. His interdisciplinary expertise positions him at the intersection of neuroscience, audiology, neuroengineering, acoustics, and digital health, contributing to research aimed at advancing auditory assessment and intervention technologies.

Prof. Elbert E. N. Macau is a Full Professor at the Federal University of São Paulo (UNIFESP), Brazil, and a CNPq Level 1A Research Productivity Fellow. His research focuses on nonlinear dynamics, complex systems, complex networks, synchronization, mathematical modeling, data analysis, and computational approaches. ResearchGate His work has significant relevance to computational neuroscience and neural systems, particularly through research on neuronal network synchronization, neural dynamics, and mathematical modeling of neuronal systems. His research has examined how synaptic currents influence synchronization in networks of coupled neurons, with applications to understanding collective behavior and information processing in neural networks. FAPESP Prof. Macau has also contributed to research involving neural network models, brain-related synchronization, signal processing, and computational methods, making his expertise particularly relevant to areas such as Computational Neuroscience, Neurotechnology, Brain Sciences, Neurobiology, AI in Neuroscience, and Neural Networks. He has served as an Associate Editor for Frontiers in Computational Neuroscience and other scientific journals. FAPESP He holds degrees in Electronic Engineering from the Aeronautics Institute of Technology (ITA) and completed postdoctoral research at the University of Maryland. His interdisciplinary career bridges engineering, applied mathematics, computational science, nonlinear systems, and neuroscience.