Full Professor of Statistics at Miguel Hernández University (UMH), specialised in Bayesian modelling, Machine Learning, Artificial Intelligence and spatio-temporal statistics. Member of IMCIDIA, CIO, STATSALUT, the Artificial Intelligence Research Group (Grupo IA – UMH), and VaBaR (Valencia Bayesian Research Group).

I have authored more than 80 peer-reviewed papers in statistics, AI/ML, ecology, climate sciences, epidemiology and clinical modelling. My work integrates principled Bayesian inference with modern AI/ML approaches for predictive analytics, environmental modelling, biomedical research and data-driven decision making.

• AI & Machine Learning (RF, BART, boosting, XAI, LLMs)
  
• Bayesian hierarchical models, INLA, SPDE, latent Gaussian models
  
• Spatio-temporal modelling, environmental forecasting, extreme events
  
• Clinical and health data analytics, survival models, CDS
  
• DEA and data-driven frontier modelling

• Environmental & ecological systems (SDMs, aquaculture risk, climate)
  
• Health sciences & epidemiology (clinical prediction, digital surgery)
  
• Agriculture, industry & socioeconomic systems

Integration of rigorous Bayesian modelling with scalable AI/ML methods to produce robust, interpretable and actionable models for complex systems under uncertainty.

Undergraduate and graduate teaching since 2005 in Statistics, Econometrics, Bayesian modelling, Data Analysis, Machine Learning, Time Series and Experimental Design.
More than 350 ECTS taught across UMH and UV.

Teaching in Master’s degrees in Public Health, Bioestadística, Neuropsychopharmacology, Teacher Training, Bioestadística (UV) and Computational Statistics & Data Science (UMH).

Instructor in specialised courses for public administrations in the Valencian Community on:
- Generative AI
- Prompt Engineering
- LLM-based document analysis
- AI ethics and responsible use in government workflows

Supervision of 3 doctoral theses in Bayesian modelling, environmental analytics, efficiency analysis and health sciences, multivariate frontier estimation.
Ongoing supervision in Bayesian diagnostic modelling-

Supervision of doctoral theses in Bayesian modelling, environmental analytics, efficiency analysis and health sciences, and multivariate frontier estimation.

Ongoing supervision in Bayesian diagnostic modelling, and extreme-event modelling.

Direction of more than 40 MSc / TFM / TFG works across Public Health, Bioestadística, Data Science, Environmental Modelling and Clinical Analytics.

More than 80 peer-reviewed publications in international journals (JCR/WoS/Scopus) spanning statistics, ecology, health sciences, AI/ML and environmental sciences.
Selected publications available on Google Scholar and ORCID.

Statistical Editor of Public Health Nutrition (Cambridge University Press).
Reviewer for multiple journals in statistics, AI/ML, ecology and health sciences.
Evaluator for national and regional research agencies.

Participation in regional, national and European research projects in Bayesian modelling, climate-risk mitigation in aquaculture, environmental analytics, health data modelling and AI applications.

Principal Investigator in climate-risk aquaculture modelling (MODESTA – ThinkInAzul).

Collaborations with hospitals, environmental agencies, research centres and industry (e.g., AVRAMAR, UMH–FISABIO STATSALUT, public health institutions).

Consulting in statistical modelling, machine learning, environmental analytics, clinical studies, efficiency analysis and data-driven decision systems.

Development and adoption of AI/ML workflows, explainability tools, predictive systems and LLM-based automation in public administration and private organisations.

Roles in academic management, committees, coordination and programme evaluation at UMH.

Multiple DOCENTIA-UMH Teaching Excellence recognitions and Talento Docente awards.

Member of:
- Grupo IA – Artificial Intelligence Research Group (UMH)
- VaBaR – Valencia Bayesian Research Group
- SEIO
- IBS – Spanish Region

• Sánchez-Guillén, L., Lozano-Quijada, C., Soler-Silva, Á., et al., Barber, X. (2024).
  A calculator for musculoskeletal injuries prediction in surgeons: a machine learning approach.
  Surgical Endoscopy, 6577–6585.

• Fuster-Alonso, A., Mestre-Tomás, J., Baez, J.C., Pennino, M.G., Barber, X., et al. (2025).
  Machine learning applied to global scale species distribution models.
  Scientific Reports, 15, 37534.

• Polotskaya, K., Muñoz-Valencia, C., Rabasa, A., Quesada-Rico, J.A., Orozco-Beltrán, D., Barber, X. (2024).
  Bayesian Networks for the Diagnosis and Prognosis of Diseases: A Scoping Review.
  Machine Learning and Knowledge Extraction (MAKE), 6(2), 1243–1262.

• España, V.J., Aparicio, J., Barber, X. (2025).
  An adaptation of Random Forest to estimate convex non-parametric production technologies: an empirical illustration in education.
  International Transactions in Operational Research, 32(5), 2523–2546.

• España, V.J., Aparicio, J., Barber, X. (2025).
  Estimating production technologies using multi-output adaptive constrained enveloping splines.
  Computers & Operations Research, 107242.

• Esteve, M., España, V.J., Aparicio, J., Barber, X. (2022).
  eat: An R Package for fitting Efficiency Analysis Trees.
  The R Journal, 14(3), 249–281.

• España, V.J., Aparicio, J., Barber, X., Esteve, M. (2023).
  Extending Multivariate Adaptive Regression Splines to estimate production functions in DEA.
  European Journal of Operational Research, 312(2), 684–699.

• Barber, X., Conesa, D., López-Quílez, A., Martínez-Minaya, J., Paradinas, I., Pennino, M. (2021).
  Incorporating biotic information in Species Distribution Models: A coregionalised Bayesian approach.
  Mathematics, 9, 417.

• Barber, X., Conesa, D., López-Quílez, A., Morales, J. (2019).
  Multivariate bioclimatic indices modelling: A coregionalised approach.
  JABES, 24(2), 225–244.

• Martinez-García, M., Rabasa, A., Barber, X., et al. (2021).
  Key factors affecting unwillingness to be confined during COVID-19.
  Scientific Reports, 11, 18626.

• Oliver, N., Barber, X., Roomp, K., Roomp, K. (2020).
  Assessing the Impact of the COVID-19 Pandemic in Spain: Online Survey Analysis.
  Journal of Medical Internet Research, 22(9), e21319.

• Figueira, M., Barber, X., Conesa, D., López-Quílez, A., Martínez-Minaya, J., Pennino, M. (2024).
  Bayesian feedback in ecological sciences.
  Ecological Informatics, 84, 102858.

• Fernández-Gómez, L., Sánchez-Zapata, J.A., Donázar, J.A., Barber, X., Barbosa, J.M. (2023).
  Ecosystem productivity drives breeding success under changing grazing pressure.
  Science of the Total Environment, 168553.

• Carmen-Rincón, M., Sánchez-Zapata, J.A., Donázar, J.A., Barber, X., et al. (2024).
  Long-term vegetation responses to climate under rewilding vs traditional grazing.
  Landscape Ecology, 39.

• Rocha, D., Jordán, M., Barber, X., et al. (2022).
  XRD fingerprinting to study burned soils.
  Minerals, 12, 1402.

• Gomis, M.P., Pérez-Murcia, M.D., Barber, X., et al. (2022).
  Palm-derived substrates for seedling production.
  Agronomy, 12, 1377.

• Guilabert, F.J., Barber, X., Pérez-Murcia, M.D., et al. (2021).
  Green waste streams: assessing co-composting scenarios.
  Agronomy, 11, 1870.

• Fernández-Candela, A., Barber, X., López-Rodríguez-Arias, F., et al. (2025).
  Early prediction of postoperative infection after cytoreductive surgery.
  World Journal of Gastrointestinal Surgery, 17(5).

• Acosta-Mérida, M.A., Sánchez-Guillén, L., Gallego, M.Á., Barber, X., et al. (2025).
  Data governance and digital surgery: challenges and opportunities.
  Cirugía Española (Eng. Edition).

• Soler-Silva, A., Sánchez-Guillén, L., Blanco-Antona, F., Barber, X., et al. (2025).
  Predictors of complications after ileocecal resection in Crohn’s disease.
  Techniques in Coloproctology, 29, 61.

• Quesada, J.A., López-Pineda, A., Orozco-Beltrán, D., Barber-Vallés, X., et al. (2024).
  Diabetes as a cause of premature death in Spain.
  Primary Care Diabetes, 2024.

• Sánchez-Guillén, L., Lillo-García, C., Barber, X., et al. (2024).
  Telehealth acceptance: The TELECOVID study.
  Updates in Surgery, 2024.

• Aguilar-Martínez, M.M., Sánchez-Guillén, L., Barber-Vallés, X., et al. (2023).
  Long-term evaluation of fistulotomy and sphincteroplasty (FIPS).
  Diseases of the Colon & Rectum, 27(6), 443–451.

• Bosch-Ramírez, M., Sánchez-Guillén, L., Barber, X., et al. (2023).
  PTNS for faecal incontinence: long-term outcomes.
  Techniques in Coloproctology, 27(6), 443–451.

• Herlin, M., Sánchez, I., Esteban, J., Barber, X., et al. (2021).
  Bone toxicity induced by TCDD: causal analysis.
  Reproductive Toxicology, 105, 25–43.

• Sánchez-Guillén, L., Soriano-Irigaray, L., López-Rodríguez-Arias, F., Barber, X., et al. (2021).
  Peripheral parenteral nutrition in enhanced recovery for colorectal surgery.
  Journal of Clinical Medicine, 10(16), 3647.

• López-Rodríguez-Arias, F., Sánchez-Guillén, L., Lillo-García, C., Barber, X., et al. (2021).
  Body composition & parenteral nutrition.
  Nutrients, 13(9).

• Arroyo, A., Sánchez-Guillén, L., Parra, P.A., García-Catalá, L., Peña-Ros, E., Barber, X., et al. (2020).
  Photodynamic therapy for complex anal fistula.
  Lasers in Surgery and Medicine, 52, 503–508.

• Senabre-Gallego, J.M., Rosas, J., Marco-Mingot, M., García-Gómez, J.A., Barber-Vallés, X., et al. (2019).
  Monitoring serum adalimumab in axial spondyloarthritis.
  Rheumatology International, 39(5), 841–849.