Bio: Satej Soman is a PhD student at the UC Berkeley School of Information. Prior to his doctoral studies, Satej advised governments and NGOs in South and South-east Asia on COVID policy response, designed participatory urban planning tools for informal settlement activists in Western and Sub-saharan Africa, led engineering teams building data management platforms in the private sector, 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 a M.S. in Computational Analysis & Public Policy from the University of Chicago. In his spare time, Satej enjoys creating generative art and going to live comedy and music shows.
Research: Satej's research is focused on the use of multi-modal and high-dimensional data sources (e.g. satellite imagery, digital traces) to answer economic and policymaking questions.
Fields of Interest: Computational social science, Remote sensing, Machine learning, Bayesian inference
Website: www.satejsoman.com
Publications:
Vaccine Allocation Priorities Using Disease Surveillance and Economic Data
epimargin: A Toolkit for Epidemiological Estimation, Prediction, and Policy Evaluation
Assessing the burden of COVID-19 in developing countries: Systematic review, meta-analysis, and public policy implications.
Systems architecture for real time epidemiological prediction and control
Mansueto Institute for Urban Innovation Research Paper No. 24, 2020
Worldwide detection of informal settlements via topological analysis of crowdsourced digital maps
Adaptive control of COVID-19 outbreaks in India: Local, gradual, and trigger-based exit paths from lockdown
