About Me
I am a Ph.D. candidate in the Department of Agricultural and Applied Economics at the University of Georgia (UGA), specializing in advanced causal inference, and currently work as a Consultant with the World Bank’s Gender and Africa Gender Innovation Lab (GIL) teams. My work is centered around a fundamental question: How do incentives, behaviors, and market environments shape economic opportunity and welfare, and how can this evidence lead to better-designed policies and platforms?
I take a data-driven, evidence-based approach to problem-solving, with applications in the areas of labor, gender, health & mental well-being, and social behavior. This research spans Sub-Saharan Africa and South Asia through field experiments and program evaluations, and European and American contexts using observational and panel data with quasi-experimental causal inference designs.
My work employs econometric modeling and advanced experimental as well as quasi-experimental methods to estimate the causal effects of policies, programs, and labor market conditions on individual and household decisions, particularly in settings where evidence can strategically inform both public policy and technology-enabled environments.
For nearly a decade, I have worked closely with teams at the World Bank and the International Food Policy Research Institute (IFPRI), supporting projects from the initial problem framing to the point where results inform real strategic and policy decision-making. My role is integrative moving between the field, the data, and the decision table. This involves designing experiments and sampling, building and managing large-scale data pipelines and developing complex econometric and causal models to translate evidence into decision-insights for markets, users and policymakers.
I have experience managing field personnel, mentoring research assistants, and partnering with a range of institutions from federal, state, and local government agencies to NGOs and international organizations. My focus is always on fostering strong collaboration and ensuring data quality to ground rigorous analysis.
Proficient in R, Python, Stata, and SPSS, I have hands-on experience analyzing large-scale data from experimental, administrative, and observational sources across the full quantitative workflows.
A core part of my work is translating complex empirical findings into clear, defensible insights. I achieve this through technical reports, peer-reviewed journal articles, and accessible policy briefs, assisting stakeholders in making informed choices about resource allocation and real-world impact.