Dr. Joshua T. Vogelstein PhD, Neuroscience

Dr. Vogelstein is a preeminent big data and machine learning expert within the fields of neuroscience, statistics and computer science. As an expert in all three fields, he conducts research at their intersecting points, to enable hybrid vigor from cross-fertilization of ideas.

His research focuses on wide data (low sample size and high-dimensional data) as well as foundational theory and methods for attributed networks and populations of networks, especially within neuroscience and brain connectivity (connectomics).

Currently, he is an Assistant Professor in Biomedical Medical Engineering at Johns Hopkins University, and core faculty in both the Institute for Computational Medicine and the Center for Imaging Science, as well as a member of the Kavli Neuroscience Discovery Institute.

Prior to his role at Johns Hopkins, Dr. Vogelstein was a Postdoctoral Fellow in Applied Mathematics and Statistics at JHU and was later appointed an Assistant Research Scientist and member of the Institute for Data Intensive Science and Engineering. He then spent 2 years at Information Initiative at Duke University.

Dr. Vogelstein’s research has been featured in a number of prominent scientific and engineering journals and conferences including Annals of Applied Statistics, IEEE PAMI, NIPS, SIAM Journal of Matrix Analysis and Applications, Science Translational Medicine, Nature Methods, and Science.

Dr. Vogelstein received a B.S degree from the Department of Biomedical Engineering (BME) at Washington University in St. Louis, MO in 2002, a M.S. degree from the Department of Applied Mathematics & Statistics (AMS) at Johns Hopkins University (JHU) in Baltimore, MD in 2009, and a Ph.D. degree from the Department of Neuroscience at JHU in 2009.