Thierry Warin, PhD

Hi! I’m Thierry Warin, Professor of Data Science for Global Transformations at HEC Montreal, principal investigator of the World Economy theme at CIRANO and Fellow at the Digital, Data and Design (D^3) Institute at Harvard Business School. I am also the founder of quantum simulations. I am an alumnus of the Harvard Business Analytics Program (HBAP 2020) and PhD from Essec Business School (2000).

Short Bio

Thierry Warin is a professor of data science for international business whose research trajectory has progressively shifted from conventional econometric analysis toward a computationally intensive exploration of economic complexity. Rooted in early work on fiscal integration and monetary union, his scholarship now integrates network theory, natural-language processing, and retrieval-augmented generation to interrogate how information flows, algorithmic coordination, and technological change reshape economic and social systems. Throughout this evolution he has sought to make methodological innovation endogenous to inquiry, developing reproducible toolkits—such as metadata-driven systematic reviews and domain-specific R packages—that render large, heterogeneous corpora analytically tractable.

Research

I am an economic-complexity scholar who harnesses advanced data-science techniques to integrate structured and unstructured data, thereby elucidating the latent capabilities that drive economic evolution. Building on Hidalgo and Hausmann’s (2009) product-space framework, I employ information-theoretic metrics—such as entropy and proximity indices on harmonized trade and financial datasets—to quantify the diversity and interconnectedness of productive activities (Warin & Stojkov, 2023). Simultaneously, I leverage machine-learning and natural-language–processing pipelines—ranging from structural topic modeling of central-bank speeches to sentiment analysis of social-media narratives—to extract discursive signals that both reflect and shape institutional capacities (De Marcellis-Warin et al., 2023; Melchior, Warin, & Oliveira, 2025).

My current agenda positions data science as a lever to renew the social sciences. By coupling high-dimensional prediction with theory-guided structural modelling, I examine phenomena ranging from ethical standard convergence among multinational technology firms to digital-twin applications in industrial operations. This commitment to methodological pluralism is underpinned by an open-science ethos: code and data are systematically disseminated to facilitate cumulative knowledge building. In pursuing these lines of inquiry, I aim to demonstrate that rigorous, transparent computational methods can augment the explanatory power of social-science theories and enable scholars to engage, with greater fidelity, the complexity of contemporary global transformations.

References

De Marcellis-Warin, N., Kouloukoui, D., & Warin, T. (2023). Mapping global conversations on sustainable development through natural language processing. Journal of Cleaner Production, 414, 1–11.

Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570–10575.

Marty, F., & Warin, T. (2025). Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement. Journal of Economy and Technology, 1–19.

Melchior, C., Warin, T., & Oliveira, M. (2025). Investigating COVID-19-related fake-news sharing on Facebook: A mixed-methods approach. Technological Forecasting and Social Change, 213, 1–19.

Warin, T. (2021). Global research on coronaviruses: Metadata-based analysis for public health policies. JMIR Medical Informatics, 9(11), 1–28.

Warin, T. (2024). Access Statistics Canada’s open economic data for statistics and data science courses. Technology Innovations in Statistics Education, 15(1), 1–20.

Warin, T., & Stojkov, A. (2023). Sovereign bond yield differentials across Europe: A structural entropy perspective. Entropy, 25(4), 1–12.

Teaching

Visit my courses and some pedagogical innovations. I have created a platform (also full of code!) for my student as well as a data platform Mondo international.

Students supervision

Philanthropic activities

  • I am the former founding president of edhaiti, an NGO I started in 2011 after a mission in Haïti for the Inter American Development Bank following the terrible 2010 earthquake. At the onset of the Covid-19 pandemic, I also created the maclasseenligne.org and Humanités numériques projects (see the EdTech menu).
  • I am currently working on Science des données au féminin en Afrique with researcher Bernice Bancole. It is a francophone initiative targeting 200 young ladies in Benin, etc. We provide a two-year long program, solving issues using R and other languages => data science for humanity.

Thierry Warin, PhD

Hi! I’m Thierry Warin, Professor of Data Science for Global Transformations at HEC Montreal, principal investigator of the World Economy theme at CIRANO and Fellow at the Digital, Data and Design (D^3) Institute at Harvard Business School. I am also the founder of quantum simulations. I am an alumnus of the Harvard Business Analytics Program (HBAP 2020) and PhD from Essec Business School (2000).

Short Bio

Thierry Warin is a professor of data science for international business whose research trajectory has progressively shifted from conventional econometric analysis toward a computationally intensive exploration of economic complexity. Rooted in early work on fiscal integration and monetary union, his scholarship now integrates network theory, natural-language processing, and retrieval-augmented generation to interrogate how information flows, algorithmic coordination, and technological change reshape economic and social systems. Throughout this evolution he has sought to make methodological innovation endogenous to inquiry, developing reproducible toolkits—such as metadata-driven systematic reviews and domain-specific R packages—that render large, heterogeneous corpora analytically tractable.

Research

I am an economic-complexity scholar who harnesses advanced data-science techniques to integrate structured and unstructured data, thereby elucidating the latent capabilities that drive economic evolution. Building on Hidalgo and Hausmann’s (2009) product-space framework, I employ information-theoretic metrics—such as entropy and proximity indices on harmonized trade and financial datasets—to quantify the diversity and interconnectedness of productive activities (Warin & Stojkov, 2023). Simultaneously, I leverage machine-learning and natural-language–processing pipelines—ranging from structural topic modeling of central-bank speeches to sentiment analysis of social-media narratives—to extract discursive signals that both reflect and shape institutional capacities (De Marcellis-Warin et al., 2023; Melchior, Warin, & Oliveira, 2025).

My current agenda positions data science as a lever to renew the social sciences. By coupling high-dimensional prediction with theory-guided structural modelling, I examine phenomena ranging from ethical standard convergence among multinational technology firms to digital-twin applications in industrial operations. This commitment to methodological pluralism is underpinned by an open-science ethos: code and data are systematically disseminated to facilitate cumulative knowledge building. In pursuing these lines of inquiry, I aim to demonstrate that rigorous, transparent computational methods can augment the explanatory power of social-science theories and enable scholars to engage, with greater fidelity, the complexity of contemporary global transformations.

References

De Marcellis-Warin, N., Kouloukoui, D., & Warin, T. (2023). Mapping global conversations on sustainable development through natural language processing. Journal of Cleaner Production, 414, 1–11.

Hidalgo, C. A., & Hausmann, R. (2009). The building blocks of economic complexity. Proceedings of the National Academy of Sciences, 106(26), 10570–10575.

Marty, F., & Warin, T. (2025). Deciphering algorithmic collusion: Insights from bandit algorithms and implications for antitrust enforcement. Journal of Economy and Technology, 1–19.

Melchior, C., Warin, T., & Oliveira, M. (2025). Investigating COVID-19-related fake-news sharing on Facebook: A mixed-methods approach. Technological Forecasting and Social Change, 213, 1–19.

Warin, T. (2021). Global research on coronaviruses: Metadata-based analysis for public health policies. JMIR Medical Informatics, 9(11), 1–28.

Warin, T. (2024). Access Statistics Canada’s open economic data for statistics and data science courses. Technology Innovations in Statistics Education, 15(1), 1–20.

Warin, T., & Stojkov, A. (2023). Sovereign bond yield differentials across Europe: A structural entropy perspective. Entropy, 25(4), 1–12.

Teaching

Visit my courses and some pedagogical innovations. I have created a platform (also full of code!) for my student as well as a data platform Mondo international.

Students supervision

Philanthropic activities

  • I am the former founding president of edhaiti, an NGO I started in 2011 after a mission in Haïti for the Inter American Development Bank following the terrible 2010 earthquake. At the onset of the Covid-19 pandemic, I also created the maclasseenligne.org and Humanités numériques projects (see the EdTech menu).
  • I am currently working on Science des données au féminin en Afrique with researcher Bernice Bancole. It is a francophone initiative targeting 200 young ladies in Benin, etc. We provide a two-year long program, solving issues using R and other languages => data science for humanity.