Twenty-five years of work — 97 articles, 12 books, 27 chapters and more than 270 conference presentations — moving from conventional econometrics toward computationally intensive readings of economic complexity: network theory, NLP, geoAI and machine learning on the ninety percent of the world’s information that is unstructured.
Every entry is searchable and filterable, with DOIs and links to the source.
Computational methods — NLP, machine learning, geoAI and digital twins — turned on economic questions, reading unstructured data at scale and making methodological innovation endogenous to inquiry.
Industrial organization for the algorithmic economy — pricing algorithms, platform dynamics and the risk of collusion in AI-mediated markets, and the antitrust and regulatory response.
How information flows and digital discourse shape institutional legitimacy and public perception — central-bank communication, social-media analysis, disinformation, and the climate and ESG transition.
The international economy under strain — monetary integration, global value chains and trade corridors, digital sovereignty and the new geoeconomics of industrial policy.
Over $6.5M as PI and co-PI — anchored by the $5.2M Great Lakes–St. Lawrence corridor — with more again on national programs as collaborator.
Eight R packages, 54,000+ CRAN downloads, turning closed institutional data into reproducible pipelines.
From BAA to PhD in R, Python and QGIS — geospatial data science, quantitative methods and the platform economy.