What would it cost to end extreme poverty?
3:00 PM to 4:00 PM
CSB 453
Roshni Sahoo
We study poverty minimization via direct transfers, framing this as a statistical learning problem while retaining the information constraints faced by real-world programs. Using nationally representative household consumption surveys from 34 countries that together account for 76% of the world’s poor, we estimate that reducing the poverty rate to 1% (from a baseline of 13%) would cost $211B nominal per year. This is 4.0 times the corresponding reduction in the aggregate poverty gap, but only 19% of the cost of universal basic income. Extrapolated globally, the results imply a cost of 0.28% of global GDP to (approximately) end extreme poverty.
Roshni Sahoo is assistant professor in the Decision, Risk, and Operations Division at Columbia Business School. She works on data-driven decision making for social impact. Her research develops statistical methodology to address challenges in public health and economic development, combining tools from machine learning, causal inference, and optimization. Her work has appeared in leading operations research journals (such as Operations Research) and machine learning conferences (such as NeurIPS and ICLR), and has been featured by media outlets including The Economist and Vox. Roshni completed her PhD in Computer Science at Stanford University in 2026. She also received Bachelor of Science degrees in Computer Science and Mathematics at MIT in 2020.
Organized by the AI in the Public Interest group and the DAPLab
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Nvidia Virtual Info Session Virtual
4:00 PM to 5:00 PM
Virtual
Hear from Columbia University alumni as they discuss their journey through college to a career in tech. We'll spend time talking about career opportunities at NVIDIA and how to navigate the recruiting progress.
For more information about the company, please visit the company website: https://www.nvidia.com/en-us/. Registration Information is posted on Handshake and will be shared via email.
*EVENT AUDIENCE: CS/CE Engineering Graduate Students, PhD, Bridge Students, and CS AI Concentrations
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