Wiliam Chapman

I research computation through dynamics to develop neurally inspired artificial intelligence (NeuroAI). By synthesizing computational neuroscience, dynamical systems, electrical engineering, and machine learning, I discover and implement mechanisms of coordinated computation across scales.

Currently, I am a researcher in Neuromorphic and Cognitive Computing at Sandia National Labs. Here, I lead projects on physics-based computation in emerging hardware (physical neural networks), graph neural networks for scientific computing, and physics-informed neural networks.

My work is grounded in the study and functional abstraction of biological circuits. During my PhD in Computational Neuroscience at Boston University with Michael Hasselmo, I developed models of neocortical microcircuits to demonstrate self-supervised learning via predictive coding. Previously, I researched neural mechanisms of attention and hyperdimensional neurosymbolic computing with Randy O’Reilly at the University of Colorado Boulder. My technical foundation is in biomedical and electrical engineering, ranging from microelectronics for lab-on-a-chip applications to predictive modeling for Alzheimer’s Disease detection.