About

I’m an economist who applies data science and machine learning to economic analysis. I hold a B.A. in economics from Emory University in the US and an M.Sc. in economics from the University of Bonn in Germany, where my thesis applied machine learning to causal inference with large, complex datasets.

My work focuses on using machine learning to evaluate economic policy and to support the clean energy transition in emerging economies. As an economics researcher at the Wharton School, I co-developed a dataset for evaluating the impact of land protection policies in the EU. Before that, as a research assistant at the United Nations University Institute for Environment and Human Security, I used cluster analysis to identify stakeholder mindsets on urban sustainability in Latin America.

I now work as an economic consultant, focusing on applied economics, including time series forecasting, cost modeling and statistical analysis, and building data-driven solutions for clients across a range of industries.

This site collects my research and projects applying data science to economics, energy and the environment.

All views expressed on this website are my own and do not necessarily reflect the views or policies of any organization, employer or entity I am associated with, unless explicitly stated.