Ricardo Tiosso Panassiol

Ricardo Tiosso Panassiol holds a Ph.D. in Neuroscience and Behavior from the University of São Paulo (2025), with a focus on Computational Neuroscience, under the supervision of Prof. Dr. Francisco Javier Ropero Peláez. He also holds a Masters degree in Experimental Psychology from USP (2017), with an emphasis on Sensory Psychophysiology. He earned his Bachelor's degrees in Psychology from the Federal University of Mato Grosso do Sul (UFMS, 2014) and in Law from Universidade AnhangueraUNIDERP (2012).With experience in behavioral, neurophysiological, and computational phenomena, he has worked with animal conditioning, electrophysiological recordings of the retina, and the analysis of perceptual activity in the visual system. His current research integrates principles from systems neuroscience, artificial intelligence (AI), and neuroengineering in the phenomenological computational modeling of neural circuitsparticularly thalamocortical networks. Using simulations with bioinspired artificial neural networks, he investigates orthogonalization and pattern completion, as well as the classification, integration, and sequential construction of neural coding. By combining brain biology with contemporary AI tools, his work contributes to the development of hybrid frameworksboth theoretically robust and technologically applicablealigned with the principles of NeuroAI, with potential applications in brain-computer interfaces, neuroassistive devices, and adaptive processing algorithms.Professionally, he has taught undergraduate courses in the biological foundations of behavior (UCDB, 20192020) and currently works as a behavioral clinical psychologist (CRP 14/07139-0)experiences that reinforce his teaching skills and empathic communication. He is recognized for his ability to translate complex concepts into accessible language, fostering meaningful learning in diverse contexts. His work is driven by interdisciplinary integration and a creative mindset, grounded in technical rigor and focused on innovative and transformative solutions. Believing in the transformative potential of bridging psychology, neuroscience, and engineering, he actively seeks collaborations and projects that put this vision into practice.His main academic interests include: Computational Neuroscience Artificial Intelligence Systems Neuroscience Behavioral Neuroscience Neuroengineering Behavior Analysis (Source: Lattes Curriculum)