Imad El Badisy, PhD
Health Data Scientist & Computational Methodologist
I am a health data scientist and computational methodologist building software for machine learning and computational biostatistics.
My focus is turning advanced statistical and machine learning methods into reliable, open-source tools that researchers can use. Learn more from the software packages I build.
Get in touch at elbadisyimad@gmail.com or ielbadisy@cm6.ma.
About me
I hold a PhD in Biomedical Sciences from Aix-Marseille University (SESSTIM laboratory) on missing data and machine learning methods for survival analysis. I develop software and design agentic workflows that bridge statistical rigor with modern computation. See my full list on the software page.
Moroccan and French national, husband and father.
See my education and experience or download my CV (PDF).
Research
My methodological research centers on four areas:
- Scientific machine learning: machine learning methods grounded in statistical and scientific structure, with an emphasis on interpretability and reliable inference.
- Survival analysis: survival machine learning, including individualized prediction, neural survival models, RMST summaries, and trajectory phenotyping.
- Missing data imputation: machine learning imputation methods and their evaluation, particularly for survival outcomes.
- Agentic data science: LLM-based agents that plan and run statistical analysis workflows, and software designed so that these agents can use it correctly, reproducibly, and safely.
Consulting
I provide independent methodological and statistical consulting for health research teams, from study design through publication.
- Study design and analysis plan review
- Statistical methodology (survival analysis, functional data, predictive modeling)
- Evidence synthesis
- Machine learning prediction for health outcomes
- Health economics and cost-effectiveness studies
- Custom R package and tool development