Brian DePasquale

Brian DePasquale is an Assistant Professor in the Department of Biomedical Engineering and a Faculty Fellow in the Faculty of Computing & Data Sciences (CDS). He leads the Artificial and Biological Intelligence Lab and is an affiliate faculty member in the Center for Systems Neuroscience. He conducts quantitative neuroscience research at all scales, from cognitive neuroscience and circuit biophysics to protein biochemistry. He uses approaches from machine learning, dynamical systems, and probabilistic modeling to uncover neural algorithms underlying decision-making, movement, and sensory processing.

During his doctoral training at Columbia University and postdoctoral work at the Princeton Neuroscience Institute, Brian pioneered methods for constructing biologically realistic network models, establishing a bridge between networks in the brain and AI systems. In collaboration with experimental neuroscientists, his lab designs machine learning approaches to uncover structure in large neural datasets and develops artificial neural networks to understand the neural dynamics underlying computation.

Brian’s broader data science contributions include scalable software tools for state-space modeling (developed in Julia), graph neural networks and foundation models for neural chemical sensing in olfaction, and hierarchical probabilistic models of decision-making and movement. His lab’s efforts bridge computational modeling with experimental design, advancing both neuroscience and AI interpretability, and contributing to the broader “NeuroAI” community, which aims to integrate methods and insights from neuroscience and AI to both understand the brain and build more biologically inspired AI.

Brian is also an affiliate faculty member in the Neurophotonics Center and the Hariri Institute for Computing.