Marco Vinicius Bhering de Aguiar Vallim is a Ph.D. candidate in Electrical Engineering and Computing at Mackenzie Presbyterian University (São Paulo, Brazil), where he also serves as a university lecturer. He holds a Master’s degree in Electrical Engineering and Computing and undergraduate degrees in Systems Analysis and Development, Information Systems, and Economics. His research interests focus on artificial intelligence applied to decision support, epidemiological and clinical surveillance, time series forecasting, anomaly detection, and explainable and generative AI. His doctoral research investigates hybrid predictive surveillance frameworks for the early detection, forecasting, and mitigation of respiratory disease outbreaks with pandemic potential, using routinely collected health data. Marco has professional experience in data science, machine learning, and AI-driven product development, having worked as a technical product manager and data scientist in large-scale digital platforms and innovation environments. He has contributed to applied research projects in predictive modeling, process mining, and decision-support systems across public health, energy, and industrial domains. He has authored peer-reviewed publications in the areas of machine learning, predictive maintenance, and applied data science and has experience teaching undergraduate and graduate courses related to artificial intelligence, software engineering, decision support systems, and business proc