Summary
Mahdi Zarei is a research scientist and computational neuroscientist at the University of California, San Francisco, bringing over a decade of experience in machine learning, mathematical modeling, and software development. He leads AI-driven analyses of neural dynamics and connectivity, decoding neural responses to visual stimuli and CRH neuron activity, and applying graph-theoretic approaches on UCSF’s HPC to study anxiety and brain networks. His work spans brain data mining, fMRI voxel selection, ROI-based connectivity, and neuropsychiatric research, with projects ranging from schizophrenia to sensory processing. Beyond academia, he has applied mathematical modeling to energy systems and environmental monitoring, reflecting a versatile data scientist who turns theory into practical tools. Based in the San Francisco Bay Area, he holds a PhD in Information Technology and Data Mining and speaks English, Azerbaijani, Turkish, and Farsi.
11 years of coding experience
8 years of employment as a software developer
Federation University Australia