معرفی
Beniamino Hadj-Amar is a Research Fellow in the Department of Statistics at Rice University, specializing in advanced statistical methodologies with applications in neuroscience and biomedical research. His work integrates Bayesian statistical models, time series analysis, and computational techniques to address complex problems in health and cognitive science.
Education: PhD in Statistics (University of Warwick, UK), MSc in Statistics (University of Warwick, UK), and BSc in Mathematical Statistics and Data Management (University of Genoa, Italy).
Research focuses on Bayesian modeling of neural and physiological systems, including circadian rhythms, neuromodulator dynamics, and gesture phase segmentation. Recent contributions include innovative approaches to improve data quality in neuroimaging and telemetric health monitoring. His interdisciplinary work bridges statistics with neuroscience, genomics, and clinical applications.
Publications span 2019–2025, emphasizing methodological advancements in nonstationary time series, autoregressive models, and hidden Markov frameworks. His research addresses both theoretical challenges and practical applications in health informatics and systems biology.
