Lorenzo Fabbri

Perfil

Investigador cuantitativo especializado en el desarrollo de pipelines reproducibles de inferencia causal sobre datos observacionales de salud a gran escala. Formación doctoral en inferencia causal, con enfoque aplicado en cohortes longitudinales e integración multi-ómica. Con experiencia aplicada en g-methods, controles negativos, emulación de ensayos clínicos y aleatorización mendeliana en cohortes internacionales (HELIX, ATHLETE). Autor de paquetes de R en CRAN (forrest, orcidtr) y desarrollador principal del ecosistema etverse para inferencia causal reproducible y transparente.

Competencias

Software

etverse: ecosistema modular de R para inferencia causal transparente [github.com/etverse]
Software | En desarrollo
Incluye: causatr (estimación de efectos causales), negatr (análisis de controles negativos) y otros paquetes de métodos.

forrest: Publication-Ready Forest Plots [link]
Software | CRAN: Contributed Packages, 2026

orcidtr: Retrieve Data from the ORCID Public API [link]
Software | CRAN: Contributed Packages, 2026

Experiencia Académica

Postdoctoral Researcher oct 2025 – mar 2026
Barcelona Institute for Global Health | Maternal, Child and Reproductive Health Barcelona, ES

PhD Student jun 2021 – sep 2025
Barcelona Institute for Global Health | Childhood and Environment Barcelona, ES

Student Research Assistant Fellowship mar 2017 – may 2017
Università della Svizzera italiana | Faculty of Informatics Lugano, CH

Formación Académica

Diploma de Experto Universitario en Métodos Avanzados de Estadística Aplicada dic 2025 – Actual
UNED Madrid, ES

Graduate Certificate in Theoretical Statistics and Probability oct 2024 – Actual
The Open University Milton Keynes, GB

PhD Programme in Biomedicine sep 2021 – sep 2025
Universitat Pompeu Fabra | Faculty of Health and Life Sciences Barcelona, ES

M.Sc. in Quantitative and Computational Biology oct 2017 – oct 2019
Università degli Studi di Trento | CIBIO Trento, IT

B.Sc. in Biotechnology oct 2012 – feb 2016
University of Parma | Dipartimento di Scienze Chimiche, della Vita e della Sostenibilità Ambientale Parma, IT

Publicaciones Seleccionadas

1. Fabbri L, Andrušaitytė S, Basagaña X, Bhopal S, Bustamante M, Cheung RW, Gražulevičienė R, Guxens M, Kadawathagedara M, Kampouri M, Maitre L, Marquez S, Montazeri P, Myridakis A, Slama R, Thomsen C, Vrijheid M. Prenatal and childhood exposure to mixtures of environmental chemicals and adolescence attentional problems: a triangulation study. Environment International. 2025;206:109927. doi:10.1016/j.envint.2025.109927

2. Fabbri L, Robinson O, Basagaña X, Chatzi L, Gražulevičienė R, Guxens M, Kadawathagedara M, Sakhi AK, Maitre L, McEachan R, Philippat C, Pozo ÓJ, Thomsen C, Wright J, Yang T, Vrijheid M. Childhood exposure to non-persistent endocrine disruptors, glucocorticosteroids, and attentional function: A cross-sectional study based on the parametric g-formula. Environmental Research. 2025;264:120413. doi:10.1016/j.envres.2024.120413

3. Warkentin S, Stratakis N, Fabbri L, Wright J, Yang TC, Bryant M, Heude B, Slama R, Montazeri P, Vafeiadi M, Grazuleviciene R, Brantsæter AL, Vrijheid M. Dietary patterns among European children and their association with adiposity-related outcomes: a multi-country study. International Journal of Obesity. 2025;49(2):295-305. doi:10.1038/s41366-024-01657-6

4. Stratakis N, Anguita-Ruiz A, Fabbri L, Maitre L, González JR, Andrusaityte S, Basagaña X, Borràs E, Keun HC, Chatzi L, Conti DV, Goodrich J, Grazuleviciene R, Haug LS, Heude B, Yuan WL, McEachan R, Nieuwenhuijsen M, Sabidó E, Slama R, Thomsen C, Urquiza J, Roumeliotaki T, Vafeiadi M, Wright J, Bustamante M, Vrijheid M. Multi-omics architecture of childhood obesity and metabolic dysfunction uncovers biological pathways and prenatal determinants. Nature Communications. 2025;16(1). doi:10.1038/s41467-025-56013-7

5. Güil-Oumrait N, Stratakis N, Maitre L, Anguita-Ruiz A, Urquiza J, Fabbri L, Basagaña X, Heude B, Haug LS, Sakhi AK, Iszatt N, Keun HC, Wright J, Chatzi L, Vafeiadi M, Bustamante M, Grazuleviciene R, Andrušaitytė S, Slama R, McEachan R, Casas M, Vrijheid M. Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children. JAMA Network Open. 2024;7(5):e2412040. doi:10.1001/jamanetworkopen.2024.12040

Lista completa disponible en ORCID y Google Scholar.

Honores y Premios

Student Tuition Waiver [declined] jun 2024
CAUSALab Summer Courses on Causal Inference Boston, US

Outstanding Abstract by a Student sep 2022
International Society for Environmental Epidemiology Herndon, US

Formación Continua

Spring School in Causal Inference with Observational Data abr 2022
Causal Insights Leeds, GB

Computational Bayesian methods using brms in R feb 2022
Physalia Courses Berlin, DE

ELIXIR Omics Integration and Systems Biology sep 2021
National Bioinformatics Infrastructure Sweden Uppsala, SE

Advanced Statistics: Statistical Modelling ago 2021
Swiss Institute of Bioinformatics Lausanne, CH

Alpine Exposome Summer School jun 2021
INSERM Paris, FR

Metabolomics Data Processing and Data Analysis feb 2021
University of Birmingham Birmingham, GB

Mendelian Randomisation may 2020
Imperial College London London, GB

Image Analysis and Modeling of Complex Biological Dynamics sep 2017
University of Würzburg Würzburg, DE

Effective High Performance Computing Summer School jul 2017
CSCS - Swiss National Supercomputing Centre Lugano, CH

MARVEL School on Variationally Enhanced Sampling feb 2017
University of Lugano Lugano, CH

Advanced Course in Alternatives to Animal Experimentation nov 2015
University of Genoa Genoa, IT

Última actualización: mayo 2026