John P. Cunningham

John P. Cunningham is a Professor of Statistics at Columbia University's Faculty of Arts and Sciences and a core member of the Data Science Institute (DSI). His research focuses on machine learning applications in science and industry, particularly leveraging AI to understand biological intelligence and complex systems. He holds affiliations with the Foundations of Data Science, Grossman Center for the Statistics of Mind, Zuckerman Mind Brain Behavior Institute, and Center for Theoretical Neuroscience.

Education: B.S. in Computer Science (Dartmouth College), M.S./Ph.D. in Electrical Engineering (Stanford University), and postdoctoral research in Machine Learning at the University of Cambridge. His work bridges computational neuroscience, statistical theory, and scalable machine learning.

Research interests include neural decoding, Bayesian optimization, Gaussian processes, and interpretable latent variable models. Recent projects emphasize medical AI, neurotechnology, and foundational ML theory. His lab develops open-source tools for neuroscience analysis, such as Lightning Pose and BehaveNet.

Notable contributions include work on neural geometry in motor cortex, scalable Gaussian processes, and AI ethics in clinical applications. Collaborations span academia and industry, focusing on translating theoretical insights into practical solutions for healthcare and neuroscience.