🎓 Digital Humanities Research Engineer | Art Historian | Art lover | AI & Cultural Heritage Researcher
I'm a digital humanities research engineer working at the intersection of art history, cultural heritage, and artificial intelligence. I support a wide range of research projects in the social sciences and humanities, helping researchers design, implement, and apply computational methods to their research questions.
You will find here how computational methods can support research in the humanities.
- ➡️ Datasets (web scraping, metadata extraction, cleaning, normalization, and structuring)
- ➡️ Annotation pipelines (designing annotation protocols, defining research objectives, establishing clear annotation guidelines, and developing annotation environments in Label Studio)
- ➡️ Computational methods (quantitative analysis, data visualization, pattern recognition, statistical modeling, AI training, fine-tuning, and evaluation)
- ➡️ How AI transforms the production, description, circulation, and interpretation of cultural heritage data, and how AI models can be approached as cultural objects in themselves
- ➡️ Using AI to support humanities research while mobilizing humanities approaches to critically analyze datasets, models, and computational systems
- ➡️ Evaluation metrics for text and image generation, confronting computational definitions of quality and performance with critical perspectives from the social sciences and humanities
- ➡️ Maison des Sciences Sociales et des Humanités Lyon–Saint-Étienne. Research engineer supporting projects across 52 research laboratories.
- ➡️ Université Lumière Lyon 2 Teaching digital humanities tools and methods for art history students.
- ➡️ Université Jean Monnet Saint-Étienne Teaching digital humanities tools, research data methods, and computational approaches.
I also collaborate with research infrastructures and communities such as:
- Huma-Num https://www.huma-num.fr
- RnMSH https://www.msh-reseau.fr
- DataLySte https://datalyste.universite-lyon.fr/ateliers-de-la-donnee-328675.kjsp
- GANESHshttps://ganeshs.hypotheses.org
- OPERAS SIG AI https://operas-eu.org/special-interest-groups/artificial-intelligence-special-interest-group/
- Machine translation evaluation : Developing and comparing metrics to analyze and quantify machine translation outputs.
- Manuscript modeling : Knowledge graphs and semantic modeling of compilation strategies in manuscript traditions.
- Multimodal analysis : Investigating how text and image representations cohabit latent spaces, and how computational metrics help interpret these spaces.
- Metaphor detection in textual data : Designing annotation pipelines and training models to identify metaphors in translation discourse.
- Political questionnaire analysis : Statistical analysis, mapping, and synthetic data generation for social science survey research.
- Personal data in AI production : Investigating how models such as OpenAI's GPT use context to adapt responses, and how generated context can become a form of personal data representation.
- Visual data analysis in sociology : Developing computational pipelines to quantitatively analyze drawing-based sociological surveys.
- Visual data analysis for synesthesia research
- AI citation guide : Developing practical guidelines for citing AI usage in research, data management plans, and teaching.
- Giving workshops : AI prompting, annotation workflows, Label Studio, Tropy, Omeka S, and Huma-Num services.
- Developing a thesaurus of AI evaluation metrics using OpenTheso.
- Advanced Python for data analysis and research engineering
- Evaluation metrics for text, image, and multimodal analysis
- Bash scripting and systems architecture
- Semantic web and knowledge modeling
- Russian, for fun
- Women of Lyon: A digital project shedding light on women's contributions to Lyon's cultural and historical landscape.
- Research Blog — Janus.txt Reading notes and reflections on digital humanities, AI, and multimodal analysis
- Tutorial Short videos on tools and methods for SHS research