Joshua Vogelstein

Joshua Vogelstein, PhD, is an Associate Professor of Biomedical Engineering at Johns Hopkins University, affiliated with the Whiting School of Engineering. His research focuses on understanding intelligence—both biological and artificial—through the lens of shared principles. He develops statistical machine learning and big data tools to analyze neural circuits, connectomes, and large-scale biological datasets. Key collaborations include experimental neuroscientists worldwide, driving advances in connectomics and computational neuroscience.

Research interests include systems neuroscience, cognitive and computational models of intelligence, and applying machine learning to understand neural communication across scales. His lab emphasizes rigorous statistical methods and reproducible neuroimaging analysis, addressing challenges like batch effects and data reliability. Notable contributions include CloudReg for cross-modal brain registration and GraSPy for graph statistics.

Recent work explores organoid intelligence, leveraging organoid networks to model brain development and disease. Vogelstein’s team also investigates prospective learning frameworks for dynamic systems and causal inference in observational health studies. His lab maintains open-source tools like mvlearn and Neurodata’s ecosystem, advancing reproducible neuroscientific research.