Investigador postdoctoral en Epidemiología
lorenzo.fabbri92sm@gmail.com | Madrid, España | lorenzofabbri.github.io/epilorenzo | ORCID | Google Scholar | GitHub | LinkedIn | Bluesky
Epidemiología del cáncer, inferencia causal y triangulación de la evidencia.
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
Máster universitario de Análisis Económico mar 2026 – Actual
Universitat Oberta de Catalunya Barcelona, ES
Máster de Formación Permanente en Salud Pública dic 2025 – Actual
UNED Madrid, ES
Diploma de Experto Universitario en Métodos Avanzados de Estadística Aplicada dic 2025 – Actual
UNED Madrid, ES
PG Certificate in Public Health oct 2025 – Actual
London School of Hygiene & Tropical Medicine London, GB
Epidemiología Básica (PHM101)
Graduate Certificate in Theoretical Statistics and Probability oct 2024 – Actual
The Open University Milton Keynes, GB
Estadística Matemática (M347): 91/100 con distinción
PhD Programme in Biomedicine sep 2021 – sep 2025
Universitat Pompeu Fabra | Faculty of Health and Life Sciences Barcelona, ES
Tesis: Exposición temprana a contaminantes ambientales y neurodesarrollo en la infancia y la adolescencia. Directora: Prof. Martine Vrijheid
M.Sc. in Quantitative and Computational Biology oct 2017 – oct 2019
Università degli Studi di Trento | CIBIO Trento, IT
Tesis (FBK, Trento): Aprendizaje automático para predecir hepatotoxicidad inducida por fármacos. Dirigida por: Dr. Cesare Furlanello, Dr. Marco Chierici, Prof. Enrico Domenici. Estancia (HITS, Heidelberg): Aprendizaje automático y profundo para predecir cinéticas de disociación en quinasas. Dirigida por: Prof. Rebecca Wade, Dr. Daria Kokh, Prof. Raffaello Potestio. Calificación final: 110/110 con honores
M.Sc. Student in Computational Science sep 2016 – jul 2017
Università della Svizzera italiana | Faculty of Informatics Lugano, CH
Proyecto (USI, Lugano): Investigación mediante técnicas computacionales de canalopatías relacionadas con canales de sodio. Dirigido por: Prof. Vittorio Limongelli, Prof. Daniele Di Marino. (Máster no completado; traslado a la Università degli Studi di Trento.)
B.Sc. in Biotechnology oct 2012 – feb 2016
University of Parma | Dipartimento di Scienze Chimiche, della Vita e della Sostenibilità Ambientale Parma, IT
Tesis (RWTH, Aachen): Modelado farmacocinético basado en fisiología (PBPK) del ácido valproico. Dirigida por: Prof. Elena Maestri, Prof. Lars M. Blank, Dr. Henrik Cordes. Calificación final: 103/110
Master’s thesis jun 2019 – oct 2019
Fondazione Bruno Kessler | Data Science for Health Unit Trento, IT
Master’s internship mar 2019 – may 2019
HITS | Molecular and Cellular Modeling Group Heidelberg, DE
Bachelor’s thesis abr 2015 – ago 2015
RWTH Aachen University | Institute of Applied Microbiology Aachen, DE
Meritatamente 2023 mar 2024 – sep 2024
Società Unione Mutuo Soccorso
Causal Inference for Environmental Mixtures [declined] mar 2024 – jun 2024
ATHLETE
Causal Inference for Environmental Mixtures [declined] jun 2024 – sep 2024
Centro de Investigación Biomédica en Red
Meritatamente 2022 2022
Società Unione Mutuo Soccorso
Erasmus+ Traineeship Programme Scholarship mar 2019 – may 2019
University of Trento
Faculty of Informatics Scholarship sep 2016 – may 2017
Università della Svizzera italiana
Erasmus Traineeship Programme Scholarship abr 2015 – ago 2015
University of Parma
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
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
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
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
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
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
Fabbri L, Garlantézec R, Audouze K, Bustamante M, Carracedo Á, Chatzi L, Ramón González J, Gražulevičienė R, Keun H, Lau CHE, Sabidó E, Siskos AP, Slama R, Thomsen C, Wright J, Lun Yuan W, Casas M, Vrijheid M, Maitre L. Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic profiles: A panel study. Environment International. 2023;173:107856. doi:10.1016/j.envint.2023.107856
Thiel C, Cordes H, Fabbri L, Aschmann HE, Baier V, Smit I, Atkinson F, Blank LM, Kuepfer L. A Comparative Analysis of Drug-Induced Hepatotoxicity in Clinically Relevant Situations. PLOS Computational Biology. 2017;13(2):e1005280. doi:10.1371/journal.pcbi.1005280
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
Las diapositivas y materiales están en github.com/lorenzoFabbri/talks.
Transparent causal inference for observational epidemiology
Charla invitada | Colicino Group, Icahn School of Medicine at Mount Sinai (vía Zoom), ene 2025
A precision environmental health approach to childhood obesity and metabolic dysfunction: identifying biological pathways and prenatal determinants [link]
Póster | ISEE Conference Abstracts, 2024
Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in European Children [link]
Póster | ISEE Conference Abstracts, 2024
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Póster | ISEE Conference Abstracts, 2022
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Póster | EURION Cluster Annual Meeting, 2022
Childhood exposure to non-persistent endocrine disrupting chemicals and multi-omic markers in a population-based child cohort [link]
Póster | PPTOX-VII International Conference, 2022
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
Students and New Researchers Network 2022 – 2023
International Society for Environmental Epidemiology Herndon, US
Early Career Scientist Working Group 2022
COnsortium of METabolomics Studies Bethesda, US
| Categoría | Detalles |
|---|---|
| Idiomas | italiano (lengua materna), inglés (C1, IELTS 7.0), español (básico) |
| Programación | R, Python, MATLAB, C |
| Marcado | LaTeX, Quarto/RMarkdown |
| Herramientas | git, SLURM, computación científica de altas prestaciones |
| Métodos | inferencia causal (g-methods, controles negativos, emulación de ensayos clínicos, aleatorización mendeliana), análisis longitudinal y de panel, análisis de supervivencia, integración multi-ómica |
Última actualización: mayo 2026