Specialization in applied econometrics and advanced data modeling allows the extraction of meaningful insights from complex datasets. Expertise encompasses statistical computing, machine learning, data science, and computer science, enabling the integration of modern computational techniques into economic analysis. Current research focuses on enhancing traditional econometric methods through the application of AI to improve empirical research outcomes while maintaining adherence to the causal inference (CI) framework.
Learn about my academic background and research interests
I am a Research Engineer at Université Paris Nanterre and EconomiX-CNRS. My research focuses on econometric methods with applications to economics and innovation studies.
I hold a PhD in Economics from Paris Dauphine University. My work emphasizes the development and application of econometrics methods to solve real-world economic problems, particularly in the areas of innovation, firm growth, and regional development.
I regularly present my research at international conferences and collaborate with researchers from various institutions.
Research Engineer, Université Paris Nanterre (2008-Present)
Research Fellow, EconomiX-CNRS (2010-Present)
Peer-reviewed journal articles and research outputs
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