Satej Soman

Satej Soman is a PhD student at Berkeley’s School of Information whose work uses computational analysis of remotely-sensed data to study global trends in inequality, urbanization, and the built environment. His doctoral research has investigated model-driven sampling for policy-specific prediction tasks, ultra-granular estimation of socioeconomic outcomes in the developing world, and applications of Bayesian inference to public health questions. This work has been supported by the World Bank, the National Science Foundation (through the Blum Center for Developing Economies), the Center for Effective Global Action, and the Centre for Economic Policy Research.

Prior to his doctoral work, Satej

• advised governments in South and Southeast Asia on their response to the COVID-19 pandemic,
• designed participatory urban planning tools for informal settlement activists in Western and sub-Saharan Africa,
• led engineering teams building petabyte-scale data management platforms for clients in cybersecurity, insurance, healthcare, and aviation; and
• worked at a startup leveraging computer vision techniques for gesture-based interfaces.

Satej holds a B.S. in Materials Science & Engineering and Electrical Engineering & Computer Science from UC Berkeley and an M.S. in Computational Analysis & Public Policy from the Harris School at the University of Chicago.