Dr. De Pittà’s research focuses on understanding how neuron–glial interactions contribute to information processing, cognitive function, and brain resilience across the lifespan. His work combines biophysically grounded computational modelling with machine learning and high-dimensional data analysis to study neural systems across multiple spatial and temporal scales, from intracellular signalling pathways to large-scale brain circuits.
A central theme of his research is the role of astrocytes and other glial cells in shaping synaptic transmission, plasticity, and network dynamics. By developing multiscale models of glial signaling and neuron–glial communication, his lab investigates how these interactions influence memory, cognitive flexibility, and stability, and how their dysregulation contributes to neurodegenerative diseases such as Alzheimer’s disease. These models are informed by multimodal data, including brain imaging, transcriptomics, cellular neuroanatomy, and electrophysiology.
More recently, Dr. De Pittà’s research has expanded toward the development of biologically interpretable digital twins of neural systems. These computational frameworks integrate mechanistic models with AI-driven inference to simulate disease trajectories, identify biomarkers, and predict responses to therapeutic interventions. His work emphasizes explainable, physics-informed machine learning approaches compatible with clinical translation.
By bridging computational neuroscience, neuroengineering, and clinical research, Dr. De Pittà aims to develop predictive tools that support early diagnosis, personalized treatment strategies, and a deeper mechanistic understanding of cognitive aging and neurodegeneration.
Maurizio De Pittà is an Assistant Professor in the Departments of Physiology and Medical Biophysics at the University of Toronto and a Scientist at UHN's Krembil Brain Institute. He is a computational neuroscientist whose work lies at the intersection of biophysical modeling, applied mathematics, and data-driven artificial intelligence, with a particular focus on neuron–glial circuits and astrocyte physiology.
Dr. De Pittà received his PhD in Electrical Engineering from Tel Aviv University and completed postdoctoral training in theoretical and computational neuroscience at the University of Chicago and INRIA (France). Since establishing his independent research program in 2018, he has led interdisciplinary efforts to understand how interactions between neurons, glial cells, and vascular components shape brain function in health and disease. His work has contributed to the emergence of computational glioscience, a field that integrates multiscale modeling with experimental and clinical data to generate predictive theories of brain organization.
Dr. De Pittà’s research has been published in leading journals, including PNAS and Science, and supported by competitive funding from national and international agencies in Europe, Canada, and the United States. He is the co-author of the textbook Computational Glioscience (Springer) and actively contributes to training initiatives in computational neuroscience and neuro-AI. Through close collaborations with clinicians, engineers, and data scientists, his work aims to translate mechanistic insights into clinically actionable tools for neurodegenerative and age-related brain disorders.
- Assistant Professor, Department of Physiology, Temerty Faculty of Medicine, University of Toronto
- Assistant Professor, Department of Medical Biophysics, Temerty Faculty of Medicine, University of Toronto
- Adjunct Professor, Graduate Program in Neurosciences, University of the Basque Country, Spain
- Affiliated Scientist, Basque Center for Applied Mathematics, Spain