I am an independent data scientist and consultant based in Berlin, Germany. A physics graduate, with PhD, of the École normale supérieure, I have worked as a mathematical modeller, coder and developer in fundamental and applied research. My main domains of expertise are physics, infectious-disease surveillance and epidemiology. Experimental biology and visual arts have also been part of my professional life.

This lead me to live and work in five cities in four countries, and speak three languages fluently. I use the pronouns he/him. A full curriculum vitae in English can be downloaded here (pdf).

My training and the beginning of my professional career were dedicated to scientific research in physics.

I graduated from the École normale supérieure in Paris, France, in theoretical particle and statistical physics. After a Master of Arts in computer animation at the École nationale des Arts des décoratifs, Paris, I went back to scientific research and did a PhD on the experimental characterization of noise propagation in gene regulatory networks. After eight years in Paris, I came to Germany for a postdoc in Cologne on the mathematical modeling of bacterial fitness landscape and human-influenza evolution. Measurement errors and uncertainty quantification were central topics of my work in physics.

I worked as visual artist for a while (a pdf portfolio as of 2014 can be downloaded here) before getting interested by machine learning for health: A lot was happening there and it was, technically speaking, quite close to what I knew from physics. What I did discover though and interested me particularly were the techniques and applications of quantitative model evaluation. My data-science career proper started when I joined the Robert Koch Institute, Germany’s national public-health agency.

Over a few years at RKI, my colleagues and I set up and grew a data-science team that developed and maintained analysis pipelines and dashboards for infectious-disease surveillance. To be relevant, this necessitated a constant dialogue with domain experts: epidemiologists as well as public-health agents. I grew more and more aware of societal aspects of data-collection and analysis software, especially given the sensitivity of population-health surveillance. At that time pioneering work about what is broadly called “AI ethics” was gaining widespread attention.

My work at the World Health Organization (WHO) and at the Helmholtz Centre for Infection Research continued and expanded this approach. My work came to be relevant for many different populations. I also came in contact with many different data sources and types, software, and topics beyond infectious disease.

This confirmed to me that data science, from data collection and processing to statistical analysis and machine learning, to data visualization and interactive dashboards, was, in fact, a transversal topic to a variety of domains, and was often needed in self-contained projects. Thus, working as an independent developer and consultant was a great way for me to contribute to society as a data scientist.

Since May 2023 I am a staff member of WHO and work as a data scientist at the WHO Hub for Pandemic and Epidemic Intelligence in Berlin. I provide and support data analysis and visualization for public health intelligence. One focus is enhancing event-based surveillance via the survey of online articles for the EIOS community.