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Welcome to my Website! I am a postdoctoral fellow at NYU’s Center of Social Media and Politics. Previously, I was a PhD Student in Decision Science at the University of Constance (Germany) and a Research Scientist Intern at Meta Core Data Science in London (UK).

My research interests lie at the intersection of Comparative Politics, Political Methodology, and Data Science and consist in utilizing methodological advances to unravel the mechanisms of democratic representation in the 21st century. My research revolves around three pillars presented below: Theory of representation, Political risks of new technologies, and Methodological tools.

Beyond my research, I also taught numerous substantial and methodological classes in French, German, and English. I am also committed to using my technical skills for the greater good. During the 2022 French presidential election, I led the development of poliverse, a platform meant to bridge the gap between academic knowledge and citizens. Poliverse proposed short analytical briefs and interactive dashboards pertinent to the election. Additionally, I am very much engaged in fostering diversity and inclusivity in academia. I frequently collect and analyze conference data (last example was EPSA 2023) to underscore the existing and enduring disparities in political science.

Outside my academic work, I am a compulsive #rstats programmer, a below-average pianist, and a dedicated foody! I also cherish any time I can spend in the Canadian wilderness sharpening my lumberjack skills, and I can’t get enough free space, wood chopping, and maple syrup.

Learn more about my research, teaching, software and CV!

Research agenda


Democratic representation


This first axis of my research explores the implications of emerging technologies on our understanding of democratic representation. My dissertation put forth a series of theoretical models of policy-making and intra-partisan coordination. Building upon spatial models, the formal models incorporate the concept of political capital and investigates empirically how unequal distribution among representatives affects the quality of representation.

Political challenges of AI


The second avenue examines the political challenges posed by the emergence of new technologies, such as social media and recommender systems. This question bifurcates into two primary concerns. On the one hand, I seek to comprehend how artificial intelligence processes, interprets and responds to political inputs. On the other hand, I also study how citizens’ rising exposure to artificial intelligence and its eventual biases affect their political behavior.

Methodological Tools


I develop novel computational methods and tools for acquiring and analyzing political data. My primary fields of expertise relate to data engineering and text-as-data. Yet, I contribute to diverse methodological domains, including statistical modelling, survey research, web scraping, causal inference, and the general application of ML within social sciences. My technical work predominantly involves R and Python, but I am also proficient in Javascript, C++, and Bash when needed.