Reza Eghbali

Reza Eghbali is a Research Scientist currently at Meta, building upon a diverse background in optimization algorithms, machine learning, and computational neuroscience. As a PhD candidate in Electrical Engineering at the University of Washington, Reza focused on online learning challenges and applied unsupervised learning methods to data from the primate visual cortex. Previously, Reza served as a Data Science Health Innovation Fellow at the University of California, San Francisco, developing machine vision pipelines for MRI analysis and survival prediction models for CNS lymphoma patients. Reza also gained experience as a Research Fellow at the University of California, Berkeley, and worked as a Data Engineer at Cisco Tetration Analytics, where advanced online machine learning models were implemented for network security. Reza holds a Master’s Degree in Mathematics from the University of Washington and a Bachelor's Degree in Electrical and Electronics Engineering from Sharif University of Technology.