Summary
Joshua Faskowitz is a postdoctoral fellow and network neuroscientist with a decade of experience using graph theory and network science to discover, model, and analyze organizational motifs of brain architecture. He combines deep expertise in fMRI and neuroimage preprocessing with algorithmic network modeling to uncover spatiotemporal covariance patterns in brain data across large, harmonized datasets. At NIMH and previously at Indiana University and USC, he has built reproducible data pipelines and analysis tools (publicly available on his GitHub) that enable scalable, replicable network neuroscience. Known for pragmatic code, heavy use of compute clusters, and a research-first curiosity, he bridges theoretical network methods with practical image-wrangling to generate insights that are both methodologically rigorous and biologically meaningful.
11 years of coding experience
4 years of employment as a software developer
B.A. Neuroscience & Cognitive Science, Minor Marketing, B.A. Neuroscience & Cognitive Science, Minor Marketing at University of Southern California
Doctor of Philosophy - PhD, Neuroscience & Psychology, Doctor of Philosophy - PhD, Neuroscience & Psychology at Indiana University Bloomington