I am a computational neuroscientist with over 15 years of interdisciplinary research experience at the intersection of applied mathematics, biomedical data science, and artificial intelligence. My work centers on building predictive and interpretable models of brain function and dysfunction, with a particular emphasis on aging and neurodegenerative diseases such as Alzheimer’s. Drawing on multiscale modeling, machine learning, and high-dimensional data analysis, I develop physics-informed and data-driven tools to quantitatively assess brain health and disease progression.

A core tenet of my research is the integration and open sharing of large, heterogeneous datasets—from cellular signalling to clinical imaging and genomics—to enable reproducibility and cross-cohort validation. My lab actively harnesses publicly available databases and collaborates across biology, engineering, and clinical medicine to develop next-generation digital health technologies, including digital twins for individualized diagnosis and treatment planning. Current efforts include AI-based biomarker discovery, spatial analysis of brain imaging data, and mechanistic modeling of neuron-glial interactions, all aimed at accelerating precision diagnostics and therapeutic strategies in age-related cognitive decline.

Find more at https://sites.google.com/site/mauriziodepitta/.