Logan Grosenick, Ph.D.

Logan Grosenick is a postdoctoral fellow in the Department of Statistics at Columbia University. He received a Ph.D. in neurosciences from Stanford University, where he worked with Karl Deisseroth and Marc Levoy developing novel methods for volumetric functional neuroimaging of neural circuits in behaving animals. Previously he completed a Master of Science in statistics at Stanford, working with Jonathan Taylor, Brian Knutson and Patrick Suppes, to predict human behavior from single-trial fMRI, MEG and EEG data, developing interpretable models that were both accurate and yielded insight into brain function.

Grosenick is interested in developing and deploying engineering approaches to observing, controlling and understanding neuronal circuit dynamics in behaving animals. He has expertise in animal behavior, functional neuroimaging and developing large-scale machine learning approaches for modern massive data sets, and he hopes to combine these skills to build more accurate, interpretable and practically useful models of how brains function in health and disease.