Meet the Fellow: Mateo Dulce Rubio
This entry is part of our Meet the Fellow blog series, which introduces and highlights faculty who have recently joined CDS.
Meet CDS Faculty Fellow Mateo Dulce Rubio, who recently completed a PhD in Statistics and Public Policy at Carnegie Mellon University, where he was advised by Professor Edward Kennedy. Dulce Rubio received the William W. Cooper Doctoral Dissertation Award for his thesis, “Robust Nonparametric Methods for Peacebuilding.”
Dulce Rubio’s research sits at the intersection of nonparametric statistics, causal inference, optimization, and responsible machine learning. He develops flexible yet robust statistical tools for decision-making in high-stakes humanitarian and policy settings.
A core focus of his work is humanitarian demining. In collaboration with the UN Mine Action Service and UNOPS, he co-developed the RELand AI-informed system for estimating landmine contamination risk in conflict-affected areas. RELand is currently deployed in Colombia and Afghanistan to identify priority zones for mine clearance.
Dulce Rubio is now working with UNOPS to scale the system globally and expand its use across additional pillars of mine action, including victim assistance and risk education. Beyond mine action, he develops doubly robust estimators for causal inference and population size estimation under capture heterogeneity and recapture dependence, with applications in conservation, public health, and human rights.
He also studies the limitations of algorithmic decision-making from observational data, designing methods to address challenges like selection bias, missing data, privacy, and algorithmic discrimination. His approach ensures that statistical methods are not only technically sound but also ethically and socially responsible.
To view all of our current faculty fellows, please visit the CDS Faculty Fellows page on our website.
By Stephen Thomas
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