Academic Publications

How can machines learn from data?

This research line develops algorithms and computational methods that enable intelligent systems to learn from data, discover complex patterns and accelerate scientific discovery. Research spans machine learning, deep learning, scientific AI, graph neural networks, representation learning and AI for scientific applications.

2026

Armenio, Sabrina, and Manuele Leonelli. “Measuring the Inaccessible: Can AI Evaluate Accessibility in Heritage Tourism?” arXiv, 2026, arXiv:2610.38642. Preprint.

Hu, Jianyu, et al. “Learning Hamiltonians from Trajectory Data with Kernel Methods.” arXiv, 2026, arXiv:2610.17835. Preprint.

Graulich, Tim, et al. “Efficient Solutions for Optimal Transmission Switching using Graph Neural Networks.” SSRN, 2026, doi:10.2139/ssrn.7571890. Preprint.

Pulido-Barrera, D. C., You, J. E., Angonezi, A. L., Kuznetsov, A., Xu, F., Verheijen, T., Saw, A. N., Kos, P., Giorgetti, L., Molina, N., Brückner, D., & Mango, S. E. (2026). Single-molecule chromatin tracing reveals a diversity of megabase heterochromatin domains. Nature Structural & Molecular Biology.

Manzano Kharman, A., Ferraro, P., et al. (2025). Tree Proof-of-Position Algorithms. IEEE Internet of Things Journal.

Nariya, M. K., Santiago-Algarra, D., Zanardelli, G., Boudjelthia, I. K., Ye, T., Thibault-Carpentier, C., Jarriault, S., & Molina, N. (2026). Comparison of cell-cycle gene expression dynamics and mRNA kinetics across mouse and human pluripotent systems. bioRxiv.

Leonelli, M. (2026). How exceptional was the Big Three era? Extremes and persistence in men’s professional tennis. arXiv:2608.27362.

Cremaschi, A., Leonelli, M., & Varando, G. (2026). Bayesian Causal Effect Estimation for Categorical Data using Staged Tree Models. Bayesian Analysis.

Garcia Murga, A., & Leonelli, M. (2026). Disentangling spatial and structural drivers of housing prices through Bayesian networks: A case study of Madrid, Barcelona, and Valencia. Cities, 174, 107063.

Leonelli, Manuele. “Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation.” arXiv, 2026, arXiv:2606.07113. Preprint.

Gonzalez Soffner, C. R., & Leonelli, M. (2026). An analysis of factors impacting team strengths in the Australian Football League using time-variant Bradley-Terry models. International Journal of Sports Science & Coaching.

Dehghan, Arash, et al. “Joint Matching and Pricing for Crowd-Shipping with In-Store Customers.” INFOR: Information Systems and Operational Research, 2026, doi:10.1080/03155986.2026.2659467.

Fuentes-Páez, G., Molina, N., Ramos-Rodríguez, M., & Pasquali, L. (2026). SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data. BMC bioinformatics.

Shoaib, Riccomagno, Leonelli, Varando (2026). Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex. arXiv:2603.15568

Maciejowski, L., Leonelli, M. (2026). Uncovering drivers of EU carbon futures with Bayesian networks. Applied Energy, 403, 127034.

Yago Nieto, Omayra, et al. “Dual-quaternion learning control for autonomous vehicle trajectory tracking with safety guarantees.” arXiv, 2026, arXiv:2601.03097. Preprint.

Yago Nieto, Omayra, et al. “Learning-Based Decentralized Control With Collision Avoidance for Multiagent Systems.” IEEE Transactions on Control of Network Systems, vol. 13, no. 2, 2026, pp. 636–647, doi:10.1109/TCNS.2025.3649723.

Marcos-Pérez, M., Jiménez de la Jara, J., Precioso, D., Muñoz, A., Redondo-Neble, M. V., & Gómez-Ullate, D. (2025). New analysis in the preliminary design for LNG and LPG ships. Marine Structures.

Cremaschi, Andrea, Dae-Jin Lee, and Manuele Leonelli. “Will AI Take My Job? Evolving Perceptions of Automation and Labor Risk in Latin America.” arXiv preprint arXiv:2505.08841 (2025).

Leonelli, M. (2025). bnRep: A repository of Bayesian networks from the academic literature. Neurocomputing, 624, 129502.

Cremaschi, A., Lee, D., Leonelli, M. (2025). Understanding support for AI regulation: A Bayesian network perspective. Int. J. Eng. Business Management 17.

Leonelli, M. (2025). Predicting and understanding shooting performance in professional biathlon.

Leonelli, M. (2025). bnRep: A repository of Bayesian networks from the academic literature. Neurocomputing, 624, 129502.

Aceña, Lancho, De Diego, Moguerza, Lee (2025). Dynamic disagreeing neighbors: complexity estimation. Neurocomputing

Bischof, Cremaschi et al. (2025). Patient-derived acellular ascites fluid affects drug responses in ovarian cancer cell lines

Kamal, Han, Naoum-Sawaya et al. (2025). Predicting Ischemic Stroke Patients to Transfer for Endovascular Thrombectomy Using Machine Learning

Serrat-Lacasta, L., de la Cruz-Vigo, S., Leonelli, M. (2025). Evaluation of factors associated with fear and anxiety in the orthodontic treatment of adult patients. Journal of Clinical and Experimental Dentistry.

Jack S Carter, Manuele Leonelli, Eva Riccomagno and Gherardo Varando (2024). Learning staged trees from incomplete data. In Proceedings of the 12th International Conference on Probabilistic Graphical Models (PGM), pp. 231-252. PMLR. 11-13 September 2024, De Lindenberg, Nijmegen, the Netherlands.

Manuele Leonelli and Gherardo Varando (2024). Context-specific refinements of Bayesian network classifiers. In Proceedings of the 12th International Conference on Probabilistic Graphical Models (PGM), pp. 182-198. PMLR. 11-13 September 2024, De Lindenberg, Nijmegen, the Netherlands.

Leonelli, M., & Varando, G. (2024). Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear. Applied Intelligence, 54(2), 1734-1750.

Leonelli, M., & Varando, G. (2024). Structural learning of simple staged trees. Data Mining and Knowledge Discovery, 38, 1520–1544.

Harris, Cremaschi et al. (2024). From past to future: digital methods towards artefact analysis

Precioso, D., & Gómez-Ullate, D. (2023). Thresholding methods in non-intrusive load monitoring. The Journal of Supercomputing, 79(13), 14039-14062.

Leonelli, M., Ramanathan, R., & Wilkerson, R. L. (2023). Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package. Knowledge-Based Systems, 278, 110882.

Navarro-García, M., Precioso, D., Neill, K. G. O., Torres-Barrán, A., Gómez, D. G., Gallego, V., & Gómez-Ullate, D. (2023). Aggregation dynamics of tropical tunas around drifting floating objects based on large-scale echo-sounder data. Marine Ecology Progress Series, 715, 129-143.

Castelló Ferrer, E., Berman, I., Kapitonov, A., Manaenko, V., Chernyaev, M., & Tarasov, P. (2023). “Gaka-chu: a self-employed autonomous robot artist”. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 11583-11589.

Wills, Stephanie, et al. “Fragment merging using a graph database samples different catalogue space than similarity search.” Journal of Chemical Information and Modeling 63.11 (2023): 3423-3437.

Manuele Leonelli and Gherardo Varando (2023). Context-specific causal discovery for categorical data using staged trees. In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 8871-8888. PMLR. 25-27 April 2023, Palau de Congressos, Valencia, Spain.

Ballester-Ripoll, R., & Leonelli, M. (2023). The YODO algorithm: An efficient computational framework for sensitivity analysis in Bayesian networks. International Journal of Approximate Reasoning, 159, 108929.

Barbeito, I., Precioso, D., Sierra, M. J., Vegas-Azcárate, S., Fernández Balbuena, S., Vitoriano, B., … & Study Group for Non-Pharmaceutical Interventions in Spain. (2023). Effectiveness of non-pharmaceutical interventions in nine fields of activity to decrease SARS-CoV-2 transmission (Spain, September 2020–May 2021). Frontiers in Public Health, 11, 1061331.

Carli, F., Leonelli, M., & Varando, G. (2023). A new class of generative classifiers based on staged tree models. Knowledge-Based Systems, 268, 110488.

Ruiz-Zafra, A., Precioso, D., Salvador, B., Lubián-López, S. P., Jiménez, J., Benavente-Fernández, I., … & Gontard, L. C. (2023). NeoCam: An edge-cloud platform for non-invasive real-time monitoring in neonatal intensive care units. IEEE Journal of Biomedical and Health Informatics, 27(6), 2614-2624.

Leonelli, M., & Riccomagno, E. (2022). A geometric characterization of sensitivity analysis in monomial models. International Journal of Approximate Reasoning, 151, 64-84.

Butt, F. S., Wagner, M. F., Schäfer, J., & Ullate, D. G. (2022). Toward automated feature extraction for deep learning classification of electrocardiogram signals. IEEE Access, 10, 118601-118616.

Manuele Leonelli and Gherardo Varando (2022). Highly efficient structural learning of sparse staged trees. In Proceedings of the 11th International Conference on Probabilistic Graphical Models (PGM), pp. 193-204. PMLR. 5-7 September 2022, Almería, Spain.

Rafael Ballester-Ripoll and Manuele Leonelli (2022). You only derive once (YODO): Automatic differentiation for efficient sensitivity analysis in Bayesian networks. In Proceedings of the 11th International Conference on Probabilistic Graphical Models (PGM), pp. 169-180. PMLR. 5-7 September 2022, Almería, Spain.

Ballester-Ripoll, R., & Leonelli, M. (2022). Computing Sobol indices in probabilistic graphical models. Reliability Engineering & System Safety, 225, 108573.

Castelló Ferrer, E., Jiménez, E., Lopez-Presa, J. L., & Martín-Rueda, J. (2022). “Following Leaders in Byzantine Multi-Robot Systems by Using Blockchain Technology”. IEEE Transactions on Robotics.

Castelló Ferrer, E., Hardjono, T., Pentland, A. S., & Dorigo, M. (2021). “Secure and secret cooperation in robotic swarms”. Science Robotics, 4(29), eaaw3739.

How can we extract reliable knowledge from data and quantify uncertainty?

This research line develops statistical methods for inference, prediction and uncertainty quantification. Research includes Bayesian statistics, computational statistics, graphical models, causal inference, survival analysis and statistical learning, with applications in health, biology and environmental sciences.

2026

Armenio, Sabrina, and Manuele Leonelli. “Measuring the Inaccessible: Can AI Evaluate Accessibility in Heritage Tourism?” arXiv, 2026, arXiv:2610.38642. Preprint.

Maciejowski, Jan, and Manuele Leonelli. “Tail Dependence in EU Carbon Markets: Graphical Models of Extremes for EUA Futures.” Computational Economics, 2026, doi:10.1007/s10614-026-11430-8.

Barrera, J., Arribas-Gil, A., Lee, D.-J., & Meza, C. (2026). Stochastic EM Estimation and Inference for Zero-Inflated Beta-Binomial Mixed Models for Longitudinal Count Data. arXiv:2602.09279.

Lee, D.-J. (2026). Learning Latent Memory States from Longitudinal Athlete Monitoring Data. arXiv:2608.06290.

Lee, D.-J. (2026). Modelling Athletic Ageing Relative to an Estimated Performance Envelope. arXiv:2608.06635.

Galán-Arcicollar, C., Alvares, D., Najera-Zuloaga, J., et al. (2026). Bayesian joint modeling of longitudinal patient-reported outcomes and survival: an application to chronic obstructive pulmonary disease. arXiv:2609.30188.

Martínez-Minaya, J., Zumeta-Olaskoaga, L., et al. (2026). Soil texture prediction with Bayesian generalized additive models for spatial compositional data. Stochastic Environmental Research and Risk Assessment.

Lieberman-Cribbin, W., Domingo-Relloso, A., et al. (2026). The association of blood lead with cardiovascular disease incidence and mortality: findings from the Strong Heart Study cohort. Environmental Health Perspectives.

Martinez-Morata, I., Domingo-Relloso, A., Mayer, M., et al. (2025). Associations between urinary metal levels and incident heart failure: a multi-cohort analysis. JACC: Heart Failure.

Anderson, W. A., Domingo-Relloso, A., et al. (2025). Uranium exposure and kidney tubule biomarkers in the Multi-Ethnic Study of Atherosclerosis (MESA). Environmental Research.

Carbonneau, M., Li, Y., Qu, Y., Zheng, Y., Wood, A. C., et al. (2025). DNA methylation signatures of cardiovascular health provide insights into diseases. Circulation.

Mozdzen, A., Wertz, T., De Iorio, M., Cremaschi, A., et al. (2025). Repulsive mixtures via the sparsity-inducing partition prior. arXiv:2509.25860.

Cremaschi, A., Franzolini, B., De Iorio, M., et al. (2026). Bayesian semi-parametric inference for joint modelling of childhood growth and appetite phenotypes. BMC Medical Research Methodology.

Leonelli, Manuele. “Relegation, Promotion and the Components of Scoring in Water Polo.” arXiv, 2026, arXiv:2609.25894. Preprint.

Mallela, Rama Siva Sarwari, and Manuele Leonelli. “Crashing Together, Rallying Apart: Dynamic Conditional Tail Dependence in Cryptocurrency Markets.” arXiv, 2026, arXiv:2606.16840. Preprint.

Leonelli, Manuele. “Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation.” arXiv, 2026, arXiv:2606.07113. Preprint.

Iannario, Maria, Dae-Jin Lee, and Manuele Leonelli. “Modeling Psychological Profiles in Volleyball via Mixed-Type Bayesian Networks.” Journal of Big Data, vol. 13, 2026, article 99, doi:10.1186/s40537-026-01448-y.

Domingo‐Relloso, A., Zhang, Y., Wang, Z., Suchy‐Dicey, A. M., Buchwald, D. S., Navas‐Acien, A., … & Valeri, L. (2026). A Path‐Specific Effect Approach to Mediation Analysis With Time‐Varying Mediators and Time‐to‐Event Outcomes Accounting for Competing Risks. Statistics in Medicine, 45(3-5), e70425.

van den Boom, W., Cremaschi, A., & Thiery, A. H. (2026). Doubly adaptive importance sampling. Journal of Computational and Graphical Statistics, 35(1), 330-338.

García, Guerrero, Hernández-Delfin, Lee, Ellero (2026). Modeling crowd flow during stadium ingress

Gago-Carro, Imanol, et al. “Hierarchical compromise optimization of ambulance locations under stochastic travel times.” Computers & Operations Research (2025): 107208.

Cremaschi, Andrea, et al. “Postpartum Screening for Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus: A Cost-Effectiveness Analysis in Singapore.” Value in Health Regional Issues 45 (2025): 101048.

Espinosa-Moreno, Juan Carlos, Dae-Jin Lee, et al. “Modelling in-hospital length of stay: A comparison of linear and ensemble models for competing risk analysis.” PloS one 20.8 (2025): e0322101.

Larrea, Nere, et al. “Evaluating Short-Term Forecast Accuracy across COVID-19 Waves Using Penalized Spline Models.” International Journal of Medical Informatics, vol. 204, 2025, article 106079, doi:10.1016/j.ijmedinf.2025.106079.

García, A., Hernández-Delfin, D., Lee, D. J., & Ellero, M. (2025). On the modeling of dynamic queue formation and decision-making in pedestrian dynamics simulations. Simulation Modelling Practice and Theory, 103130.

Tint, Mya Thway, et al. “Differential contributions of lean and fat mass on bone mineral density in Asian women of reproductive age: The S-PRESTO study.” JBMR Plus (2025): ziaf054.

Leonelli, M. (2025). bnRep: A repository of Bayesian networks from the academic literature. Neurocomputing, 624, 129502.

Leonelli, M., Smith, J. (2025). The diameter of a stochastic matrix: A new measure for sensitivity analysis in Bayesian networks. Int. J. Approx. Reasoning, 185, 109470.

Leonelli, M., Ballester-Ripoll (2025). Global sensitivity analysis of uncertain parameters in Bayesian networks. Int. J. Approx. Reasoning.

Leonelli, M. (2025). bnRep: A repository of Bayesian networks from the academic literature. Neurocomputing, 624, 129502.

Cabral, De Iorio, Cremaschi (2025). Where does the tail start?

Cremaschi A, Wertz T, De Iorio M. “Repulsion, Chaos and Equilibrium in Mixture Models”. Journal of the Royal Statistical Society B (Statistical Methodology), 2024 Oct 10.

Galán-Arcicollar, Cristina, et al. “A joint modelling approach for longitudinal patient-reported outcomes and survival analysis.” 38th International Workshop on Statistical Modelling. 2024.

Galán-Arcicollar, C., Najera-Zuloaga, J., & Lee, D. J. (2024). Patient-reported outcomes and survival analysis of chronic obstructive pulmonary disease patients: a two-stage joint modelling approach. SORT-Statistics and Operations Research Transactions, 155-182.

Leonelli, M., & Varando, G. (2024). Robust learning of staged tree models: A case study in evaluating transport services. Socio-Economic Planning Sciences, 95, 102030.

García-García, Fernando, et al. “Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality.” Pneumonia 16.1 (2024): 12.

Filigheddu, M. T., Leonelli, M., Varando, G., Gómez-Bermejo, M. Á., Ventura-Díaz, S., Gorospe, L., & Fortún, J. (2024). Using staged tree models for health data: Investigating invasive fungal infections by aspergillus and other filamentous fungi. Computational and Structural Biotechnology Journal, 24, 12-22.

García-García, Fernando, et al. “Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods.” Computer Methods and Programs in Biomedicine 248 (2024): 108118.

García, Ander, et al. “Analysis of local density during football stadium access: Integrating pedestrian flow simulations and empirical data.” Physica A: Statistical Mechanics and its Applications 638 (2024): 129635.

García-García, Fernando, et al. “Cost-sensitive ordinal classification methods to predict SARS-CoV-2 pneumonia severity.” IEEE Journal of Biomedical and Health Informatics (2024).

Najera-Zuloaga, Lee et al. (2024). Multidimensional beta-binomial regression model: A joint analysis of PROs. Statistical Modelling 24(5)

Reyes, Najera-Zuloaga, Lee et al. (2024). A Bimodal Extension of the Beta-Binomial Distribution. Axioms 13(10), 662

Cremaschi A, De Iorio M, Kothandaraman N, Yap F, Tint MT and Eriksson J (2024) “Joint modelling of association networks and longitudinal biomarkers: an application to child obesity”. Statistics in Medicine

Kee MZL, Cremaschi A, De Iorio M, Chen H, Montreuil T, Nguyen TV, Côté SM, O’Donnell KJ, Giesbrecht GF, Letourneau N, Chan SY and Meaney MJ (2023) “Perinatal Trajectories of Maternal Depressive Symptoms in Prospective, Community-Based Cohorts across Three Continents”. JAMA Network Open, 6(10), e2339942-e2339942.

Görgen, C., Leonelli, M., & Marigliano, O. (2022). The curved exponential family of a staged tree. Electronic Journal of Statistics, 16(1), 2607-2620.

Carli, F., Leonelli, M., Riccomagno, E., & Varando, G. (2022). The R Package stagedtrees for Structural Learning of Stratified Staged Trees. Journal of Statistical Software, 102, 1-30.

Lattanzi, C., & Leonelli, M. (2021). A change-point approach for the identification of financial extreme regimes. Brazilian Journal of Probability and Statistics, 35(4), 811-837.

Leonelli, M., Riccomagno, E., & Smith, J. Q. (2020). Coherent combination of probabilistic outputs for group decision making: An algebraic approach. OR Spectrum, 42(2), 499-528.

Leonelli, M., & Gamerman, D. (2020). Semiparametric bivariate modelling with flexible extremal dependence. Statistics and Computing, 30(2), 221-236.

Görgen, C., & Leonelli, M. (2020). Model-preserving sensitivity analysis for families of Gaussian distributions. Journal of Machine Learning Research, 21(84), 1-32.

How can mathematical models describe and predict complex systems?

This research line develops mathematical models and computational methods for understanding, simulating and predicting the behaviour of complex physical and engineered systems. Research includes scientific computing, dynamical systems, numerical methods, differential geometry, mathematical physics and computational mathematics, providing mathematical foundations for simulation, control and scientific machine learning.

2026

Vaquero, Miguel, and Jorge Cortés. “On the Regularization of Primal-Dual Dynamics in Time-Dependent Nonconvex Optimization.” arXiv, 2026, arXiv:2610.19916. Preprint.

Hu, Jianyu, et al. “Learning Hamiltonians from Trajectory Data with Kernel Methods.” arXiv, 2026, arXiv:2610.17835. Preprint.

Celledoni, Elena, et al. “A Unified Discrete Gradient-SAV Framework for Structure-Preserving Integration.” arXiv, 2026, arXiv:2607.27795. Preprint.

Anahory Simoes, Alexandre, and Leonardo Colombo. “Variational Dissipative Mechanics on Lie Algebroids.” Journal of Nonlinear Science, vol. 36, 2026, article 59, doi:10.1007/s00332-026-10282-8.

Anahory Simoes, Alexandre, and Leonardo Colombo. “Robust Geometric Control of Catenary Robots under Unstructured Force Uncertainties.” arXiv, 2026, arXiv:2604.27705. Preprint.

Colombo, Leonardo, et al. “Stable Walking for Bipedal Locomotion under Foot-Slip via Virtual Nonholonomic Constraints.” arXiv, 2026, arXiv:2603.29050. Preprint.

Stratoglou, Efstratios, et al. “Nonholonomic mechanics and virtual constraints on Riemannian homogeneous spaces.” Automatica, vol. 185, Mar. 2026, article 112754, doi:10.1016/j.automatica.2025.112754.

Anahory Simoes, Alexandre, et al. “Virtual Constraint for a Quadrotor UAV Enforcing a Body-Axis Pointing Direction.” arXiv, 2026, arXiv:2602.24268. Preprint.

Yago Nieto, Omayra, et al. “Dual-quaternion learning control for autonomous vehicle trajectory tracking with safety guarantees.” arXiv, 2026, arXiv:2601.03097. Preprint.

Yago Nieto, Omayra, et al. “Learning-Based Decentralized Control With Collision Avoidance for Multiagent Systems.” IEEE Transactions on Control of Network Systems, vol. 13, no. 2, 2026, pp. 636–647, doi:10.1109/TCNS.2025.3649723.

Simoes, A. A., Marrero, J. C., & Martín de Diego, D. (2025). Mechanical Hamiltonization of unreduced 𝜙-simple Chaplygin systems. Studies in Applied Mathematics, 154, e70065.

Alsaadi, Aymen, et al. “Exascale workflow applications and middleware: An ExaWorks retrospective.” The International Journal of High Performance Computing Applications (2025): 10943420251331674.

de la Jara, J. J., Precioso, D., Bu, L., Redondo-Neble, M. V., Milson, R., Ballester-Ripoll, R., & Gómez-Ullate, D. (2025). HADAD: Hexagonal A-Star with Differential Algorithm Designed for weather routing. Ocean Engineering, 319, 120050.

Peralta-Salas, D., & Vaquero, M. (2024). Beltrami Fields with Morse Proportionality Factor. Journal of Mathematical Analysis and Applications, 128632.

Stratoglou, E., Simoes, A. A., Bloch, A., & Colombo, L. J. (2024). On the geometry of virtual nonlinear nonholonomic constraints. IEEE Transactions on Automatic Control.

Vaquero, M., Cortés, J., & de Diego, D. M. (2024). Symmetry preservation in Hamiltonian systems: Simulation and Learning. Journal of Nonlinear Science, 34(6), 115.

Ballester-Ripoll, R. (2024). Computing statistical moments via tensorization of polynomial chaos expansions. SIAM/ASA Journal on Uncertainty Quantification, 12(2), 289-308.

Garcia-Ferrero, X., Gómez-Ullate, D., Milson, R. (2024). Classification of exceptional Jacobi polynomials. arXiv:2409.02656.

Bianchin, G., Vaquero, M., Cortés, J., & Dall’Anese, E. (2024). k-dimensional Agreement in Multi-agent Systems. IEEE Transactions on Automatic Control.

Ballester-Ripoll, R., Halter, G., & Pajarola, R. (2024). High-dimensional scalar function visualization using principal parameterizations. The Visual Computer, 40(4), 2571-2588.

Precioso, D., Milson, R., Bu, L., Menchions, Y., & Gómez-Ullate, D. (2024). Hybrid search method for Zermelo’s navigation problem. Computational and Applied Mathematics, 43(4), 250.

Anahory Simoes, A., Colombo, L., de León, M., Salgado, M., & Souto, S. (2024). Euler–Lagrange–Herglotz equations on Lie algebroids. Analysis and Mathematical Physics, 14(1), 3.

Vaquero, de Diego, Cortés (2024). Designing Poisson integrators through machine learning

Anahory et al. (2024). Reduction by symmetries of contact mechanical systems on Lie groups

Bianchin, G., Vaquero, M., Cortes, J., & Dall’Anese, E. (2023). Online stochastic optimization for unknown linear systems: Data-driven controller synthesis and analysis. IEEE Transactions on Automatic Control.

Coretti-Sanchez, N., et al. “Urban Mobility Swarms: Towards a Decentralized Autonomous Bicycle-Sharing System.” 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023.

Stratoglou, Efstratios, et al. “Virtual Affine Nonholonomic Constraints.” International Conference on Geometric Science of Information. Cham: Springer Nature Switzerland, 2023.

Vaquero, M., Mestres, P., & Cortes, J. (2022). Resource-aware discretization of accelerated optimization flows: the heavy-ball dynamics case. IEEE Transactions on Automatic Control, 68(4), 2109-2124.

Simoes, A. A., Marrero, J. C., & de Diego, D. M. (2022). Exact discrete Lagrangian mechanics for nonholonomic mechanics. Numerische Mathematik, 151(1), 49-98.

Bianchin, G., Vaquero, M., Cortés, J., & Dall’Anese, E. (2021, December). Data-driven synthesis of optimization-based controllers for regulation of unknown linear systems. In 2021 60th IEEE Conference on Decision and Control (CDC) (pp. 5783-5788). IEEE.

Simoes, Alexandre Anahory, et al. “The geometry of some thermodynamic systems.” Workshop on Joint Structures and Common Foundations of Statistical Physics, Information Geometry and Inference for Learning. Cham: Springer International Publishing, 2020.

Anahory Simoes, Alexandre, et al. “On the geometry of discrete contact mechanics.” Journal of Nonlinear Science 31.3 (2021): 53.

Simoes, Alexandre Anahory, et al. “Contact geometry for simple thermodynamical systems with friction.” Proceedings of the Royal Society A 476.2241 (2020): 20200244.

How can we make optimal decisions under uncertainty?

This research line develops optimization algorithms and decision-support methodologies for complex systems. Research spans operations research, mathematical programming, optimization under uncertainty, network optimization and decision science, with applications to logistics, transportation, energy systems and digital twins.

2026

Vaquero, Miguel, and Jorge Cortés. “On the Regularization of Primal-Dual Dynamics in Time-Dependent Nonconvex Optimization.” arXiv, 2026, arXiv:2610.19916. Preprint.

Graulich, Tim, et al. “Efficient Solutions for Optimal Transmission Switching using Graph Neural Networks.” SSRN, 2026, doi:10.2139/ssrn.7571890. Preprint.

Precioso, D., Suárez, F., de la Jara, J. J., et al. (2026). BERS: Locally Optimal Continuous Algorithm for Maritime Weather Routing with Just-in-Time Arrival. arXiv:2605.31533.

Magnussen, A. E., Ghaddar, B., & Ropke, S. (2026). Decompositions for Semidefinite Programming with Reinforcement Learning. LION20.

Gómez-Casares, I., Belotti, P., Ghaddar, B., & González-Díaz, J. (2025). Solving Sparse Mixed-Integer Quadratic Problems: Application to the Unit Commitment Problem with Optimal Power Flow. arXiv:2509.18911.

Hou, S., Hu, C., Chowdary, A. S., Ghaddar, B., Naoum-Sawaya, J., & Gao, J. (2026). Deep reinforcement learning for optimizing mobile depots allocation and hybrid order dispatch in last-mile delivery under multi-participants behavioral uncertainty. Transportation Research Part E: Logistics and Transportation Review.

Manzano Kharman, A., Ferraro, P., et al. (2025). Tree Proof-of-Position Algorithms. IEEE Internet of Things Journal.

Caserta, Marco, Antonio García Romero, and Miguel Vaquero. “A Robust Chance Constrained Approach to Surgery Scheduling.” arXiv, 2026, arXiv:2608.03931. Preprint.

Anahory Simoes, Alexandre, and Leonardo Colombo. “Robust Geometric Control of Catenary Robots under Unstructured Force Uncertainties.” arXiv, 2026, arXiv:2604.27705. Preprint.

Dehghan, Arash, et al. “Joint Matching and Pricing for Crowd-Shipping with In-Store Customers.” INFOR: Information Systems and Operational Research, 2026, doi:10.1080/03155986.2026.2659467.

Colombo, Leonardo, et al. “Stable Walking for Bipedal Locomotion under Foot-Slip via Virtual Nonholonomic Constraints.” arXiv, 2026, arXiv:2603.29050. Preprint.

Stratoglou, Efstratios, et al. “Nonholonomic mechanics and virtual constraints on Riemannian homogeneous spaces.” Automatica, vol. 185, Mar. 2026, article 112754, doi:10.1016/j.automatica.2025.112754.

Anahory Simoes, Alexandre, et al. “Virtual Constraint for a Quadrotor UAV Enforcing a Body-Axis Pointing Direction.” arXiv, 2026, arXiv:2602.24268. Preprint.

Tang, Y., Ghaddar, B., Jeong, J., & Wei, Y. (2026). Optimizing charging schedules and assessing passenger commuting equilibrium for electric shuttles with shared charging stations. Transportation Research Part C: Emerging Technologies, 186, 105593.

Yago Nieto, Omayra, et al. “Dual-quaternion learning control for autonomous vehicle trajectory tracking with safety guarantees.” arXiv, 2026, arXiv:2601.03097. Preprint.

Yago Nieto, Omayra, et al. “Learning-Based Decentralized Control With Collision Avoidance for Multiagent Systems.” IEEE Transactions on Control of Network Systems, vol. 13, no. 2, 2026, pp. 636–647, doi:10.1109/TCNS.2025.3649723.

Gago-Carro, Imanol, et al. “Hierarchical compromise optimization of ambulance locations under stochastic travel times.” Computers & Operations Research (2025): 107208.

González-Rodríguez, B., Gómez-Casares, I., Ghaddar, B., González-Díaz, J., & Pateiro-López, B. (2025). Learning in Reformulation-Linearization Technique-Based Spatial Branching: Limitations of Strong Branching Imitation. INFORMS Journal on Computing.

Manzano Kharman, A., Ferraro, P., Hamedmoghadam, H., & Shorten, R. (2025). Tree Proof-of-Position Algorithms. IEEE Internet of Things Journal, 12(11), 16393–16409.

García, A., Hernández-Delfin, D., Lee, D. J., & Ellero, M. (2025). On the modeling of dynamic queue formation and decision-making in pedestrian dynamics simulations. Simulation Modelling Practice and Theory, 103130.

Manzano Kharman, A., & Sanders, W. (2025). Vulnerabilities that arise from poor governance in Distributed Ledger Technologies. ACM Digital Government: Research and Practice.

Taherkhani, G., Ghaddar, B., Alumur, S. A., & Hsu, Y. (2025). Hub Network Design for Strategic Autonomous Shuttle Deployment. IEEE Transactions on Intelligent Transportation Systems.

de la Jara, …, Precioso, D., … (2025). WeatherRouting Bench 1.0: Towards Comparative Research in Weather Routing.

Fan, Ghaddar et al. (2025). Artificial intelligence for optimization: Unleashing the potential

Croci, Jabali, Libe, Malucelli, Naoum-Sawaya (2025). A Tetris Beam Search Algorithm for the Distributor’s Pallet Loading Problem

Amirnequiee, Naoum-Sawaya, Pun (2025). Robust framework for the joint learning of consumer preferences and market segmentation

González-Rodríguez, Ghaddar et al. (2025). Polynomial optimization: Tightening RLT-based branch-and-bound schemes with conic constraints

Manzano Kharman, A., Jursitzky, C., Zhou, Q., Ferraro, P., Marecek, J., Pinson, P., & Shorten, R. (2024). An adversarially robust data-market for spatial, crowd-sourced data. ACM Distributed Ledger Technologies: Research and Practice.

Kharman, A. M., & Smyth, B. (2024). DAO Governance Protocols and their Vulnerabilities. 2024 6th Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS), 1–2.

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Kharman, A. M., Ferraro, P., Quinn, A., & Shorten, R. (2023). Robust Decentralised Proof-of-Position Algorithms for Smart City Applications. 2023 62nd IEEE Conference on Decision and Control (CDC), 112–119.

2022

The Datalab develops computational methods to improve healthcare and advance our understanding of biological systems. This programme combines artificial intelligence, statistical inference, mathematical modelling and optimization to address challenges in precision medicine, computational biology, epidemiology, environmental health and biomedical AI.

2026

Pulido-Barrera, D. C., You, J. E., Angonezi, A. L., Kuznetsov, A., Xu, F., Verheijen, T., Saw, A. N., Kos, P., Giorgetti, L., Molina, N., Brückner, D., & Mango, S. E. (2026). Single-molecule chromatin tracing reveals a diversity of megabase heterochromatin domains. Nature Structural & Molecular Biology.

Nariya, M. K., Santiago-Algarra, D., Zanardelli, G., Boudjelthia, I. K., Ye, T., Thibault-Carpentier, C., Jarriault, S., & Molina, N. (2026). Comparison of cell-cycle gene expression dynamics and mRNA kinetics across mouse and human pluripotent systems. bioRxiv.

Rizk, Joe G., et al. “Androgen Receptor Imprints Satellite Cell Stemness and Preserves Their Reservoir for Lifelong Regeneration and Optimal Repair.” Science Advances, vol. 12, no. 37, 2026, eaec8073, doi:10.1126/sciadv.aec8073.

Caserta, Marco, Antonio García Romero, and Miguel Vaquero. “A Robust Chance Constrained Approach to Surgery Scheduling.” arXiv, 2026, arXiv:2608.03931. Preprint.

Fuentes-Páez, G., Molina, N., Ramos-Rodríguez, M., & Pasquali, L. (2026). SPICEY: an R package for quantifying tissue specificity from single cell multi-omics data. BMC bioinformatics.

Domingo-Relloso, A., McGraw, K. E., Martinez-Morata, I., Zhang, Y., Schilling, K., Glabonjat, R. A., … & Valeri, L. (2026). The role of coronary artery calcification in metal-related cardiovascular disease. Environment International, 110095.

Cremaschi, Andrea, et al. “Postpartum Screening for Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus: A Cost-Effectiveness Analysis in Singapore.” Value in Health Regional Issues 45 (2025): 101048.

Espinosa-Moreno, Juan Carlos, Dae-Jin Lee, et al. “Modelling in-hospital length of stay: A comparison of linear and ensemble models for competing risk analysis.” PloS one 20.8 (2025): e0322101.

Larrea, Nere, et al. “Evaluating Short-Term Forecast Accuracy across COVID-19 Waves Using Penalized Spline Models.” International Journal of Medical Informatics, vol. 204, 2025, article 106079, doi:10.1016/j.ijmedinf.2025.106079.

Tint, Mya Thway, et al. “Differential contributions of lean and fat mass on bone mineral density in Asian women of reproductive age: The S-PRESTO study.” JBMR Plus (2025): ziaf054.

Cremaschi et al. (2025). Bayesian modelling of response to therapy and drug-sensitivity in acute lymphoblastic leukemia. Statistics in Biosciences 17(2)

Bischof, Cremaschi et al. (2025). Patient-derived acellular ascites fluid affects drug responses in ovarian cancer cell lines

Mayer, Domingo-Relloso et al. (2025). Comparison of Methods for Analyzing Environmental Mixtures Effects on Survival Outcomes

Eckhardt, Li, Bloomquist, Domingo-Relloso (2025). Extracellular vesicle-encapsulated microRNA signatures of cigarette smoking

Kamal, Han, Naoum-Sawaya et al. (2025). Predicting Ischemic Stroke Patients to Transfer for Endovascular Thrombectomy Using Machine Learning

Galán-Arcicollar, Cristina, et al. “A joint modelling approach for longitudinal patient-reported outcomes and survival analysis.” 38th International Workshop on Statistical Modelling. 2024.

Galán-Arcicollar, C., Najera-Zuloaga, J., & Lee, D. J. (2024). Patient-reported outcomes and survival analysis of chronic obstructive pulmonary disease patients: a two-stage joint modelling approach. SORT-Statistics and Operations Research Transactions, 155-182.

García-García, Fernando, et al. “Obtaining patient phenotypes in SARS-CoV-2 pneumonia, and their association with clinical severity and mortality.” Pneumonia 16.1 (2024): 12.

Filigheddu, M. T., Leonelli, M., Varando, G., Gómez-Bermejo, M. Á., Ventura-Díaz, S., Gorospe, L., & Fortún, J. (2024). Using staged tree models for health data: Investigating invasive fungal infections by aspergillus and other filamentous fungi. Computational and Structural Biotechnology Journal, 24, 12-22.

García-García, Fernando, et al. “Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods.” Computer Methods and Programs in Biomedicine 248 (2024): 108118.

Domingo-Relloso, A., Feng, Y., Rodriguez-Hernandez, Z., Haack, K., Cole, S. A., Navas-Acien, A., … & Bermudez, J. D. (2024). Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study. American Journal of Epidemiology, 193(7), 1010-1018.

García-García, Fernando, et al. “Cost-sensitive ordinal classification methods to predict SARS-CoV-2 pneumonia severity.” IEEE Journal of Biomedical and Health Informatics (2024).

Najera-Zuloaga, Lee et al. (2024). Multidimensional beta-binomial regression model: A joint analysis of PROs. Statistical Modelling 24(5)

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McGraw, Domingo-Relloso et al. (2024). Urinary metal levels and coronary artery calcification

Platania, Erb, Molina et al. (2024). Transcription processes compete with loop extrusion to homogenize promoter and enhancer dynamics

Cremaschi A, De Iorio M, Kothandaraman N, Yap F, Tint MT and Eriksson J (2024) “Joint modelling of association networks and longitudinal biomarkers: an application to child obesity”. Statistics in Medicine

2022

Dommer, Abigail, et al. “# COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol.” The international journal of high performance computing applications 37.1 (2023): 28-44.

The Datalab develops computational methods to address challenges related to climate change, sustainable infrastructure and resilient systems. Research combines machine learning, mathematical modelling, optimization and statistics to improve forecasting, planning and decision-making in energy, transportation and environmental systems.

2026

Graulich, Tim, et al. “Efficient Solutions for Optimal Transmission Switching using Graph Neural Networks.” SSRN, 2026, doi:10.2139/ssrn.7571890. Preprint.

Maciejowski, Jan, and Manuele Leonelli. “Tail Dependence in EU Carbon Markets: Graphical Models of Extremes for EUA Futures.” Computational Economics, 2026, doi:10.1007/s10614-026-11430-8.

Precioso, D., Suárez, F., de la Jara, J. J., et al. (2026). BERS: Locally Optimal Continuous Algorithm for Maritime Weather Routing with Just-in-Time Arrival. arXiv:2605.31533.

Lieberman-Cribbin, W., Domingo-Relloso, A., et al. (2026). The association of blood lead with cardiovascular disease incidence and mortality: findings from the Strong Heart Study cohort. Environmental Health Perspectives.

Martinez-Morata, I., Domingo-Relloso, A., Mayer, M., et al. (2025). Associations between urinary metal levels and incident heart failure: a multi-cohort analysis. JACC: Heart Failure.

Anderson, W. A., Domingo-Relloso, A., et al. (2025). Uranium exposure and kidney tubule biomarkers in the Multi-Ethnic Study of Atherosclerosis (MESA). Environmental Research.

Carbonneau, M., Li, Y., Qu, Y., Zheng, Y., Wood, A. C., et al. (2025). DNA methylation signatures of cardiovascular health provide insights into diseases. Circulation.

Domingo‐Relloso, A., Zhang, Y., Wang, Z., Suchy‐Dicey, A. M., Buchwald, D. S., Navas‐Acien, A., … & Valeri, L. (2026). A Path‐Specific Effect Approach to Mediation Analysis With Time‐Varying Mediators and Time‐to‐Event Outcomes Accounting for Competing Risks. Statistics in Medicine, 45(3-5), e70425.

Maciejowski, L., Leonelli, M. (2026). Uncovering drivers of EU carbon futures with Bayesian networks. Applied Energy, 403, 127034.

Lin, Y., Kopp, R. E., Reedy, A., Turilli, M., Jha, S., and Ashe, E. L.: PaleoSTeHM v1.0: a modern, scalable spatiotemporal hierarchical modeling framework for paleo-environmental data, Geosci. Model Dev., 18, 2609–2637, https://doi.org/10.5194/gmd-18-2609-2025, 2025.

de la Jara, …, Precioso, D., … (2025). WeatherRouting Bench 1.0: Towards Comparative Research in Weather Routing.

2023

Kopp, Robert E., et al. “The Framework for Assessing Changes To Sea-level (FACTS) v1. 0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change.” Geoscientific Model Development 16.24 (2023): 7461-7489.

Dommer, Abigail, et al. “# COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol.” The international journal of high performance computing applications 37.1 (2023): 28-44.

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