  | PROVERBIO, D., SKUPIN, A., & GONCALVES, J. (21 July 2023). Systematic analysis and optimization of early warning signals for critical transitions using distribution data. iScience, 26 (7), 107156. doi:10.1016/j.isci.2023.107156  Peer Reviewed verified by ORBi |
 | Heino, M., PROVERBIO, D., Marchand, G., Resnicow, K., & Hankonen, N. (2022). Attractor landscapes: a unifying conceptual model for understanding behaviour change across scales of observation. Health Psychology Review. doi:10.1080/17437199.2022.2146598 Peer Reviewed verified by ORBi |
  | Montanari, A., Freitas, L., PROVERBIO, D., & GONCALVES, J. (December 2022). Functional observability and subspace reconstruction in nonlinear systems. Physical Review Research, 4, 043195. doi:10.1103/PhysRevResearch.4.043195 Peer reviewed |
 | PROVERBIO, D. (2022). Classification and detection of Critical Transitions: from theory to data [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/52639doi:10.13140/RG.2.2.32772.40326 |
BANIASADI, M., HUSCH, A., PROVERBIO, D., fernandes arroteia, I., HERTEL, F., & GONCALVES, J. (2022). Initialisation of Deep Brain Stimulation Parameters with Multi-objective Optimisation Using Imaging Data. In Bildverarbeitung für die Medizin 2022. Springer. doi:10.1007/978-3-658-36932-3_62 Peer reviewed |
 | PROVERBIO, D., KEMP, F., MAGNI, S., OGORZALY, L., CAUCHIE, H.-M., GONCALVES, J., SKUPIN, A., & AALTO, A. (2022). Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis. Science of the Total Environment, 827, 154235. doi:10.1016/j.scitotenv.2022.154235 Peer Reviewed verified by ORBi |
 | PROVERBIO, D., NORONHA MONTANARI, A., SKUPIN, A., & GONCALVES, J. (2022). Buffering variability in cell regulation motifs close to criticality. Physical Review. E. doi:10.1103/PhysRevE.106.L032402 Peer Reviewed verified by ORBi |
 | PROVERBIO, D., KEMP, F., MAGNI, S., & GONCALVES, J. (2022). Performance of early warning signals for disease re-emergence: A case study on COVID-19 data. PLoS Computational Biology, 18 (3), 1009958. doi:10.1371/journal.pcbi.1009958 Peer Reviewed verified by ORBi |
 | PROVERBIO, D. (2022). On regime shifts in biological research [Paper presentation]. DPCS Presentations Workshop 2022, Belval, Luxembourg. |
 | Burzynski, Machado, J., AALTO, A., BEINE, M., Haas, T., KEMP, F., MAGNI, S., Mombaerts, L., PICARD, P. M., PROVERBIO, D., SKUPIN, A., & DOCQUIER, F. (December 2021). COVID-19 Crisis Management in Luxembourg: Insights from an Epidemionomic Approach. Economics and Human Biology, 43, 101051. doi:10.1016/j.ehb.2021.101051 Peer Reviewed verified by ORBi |
 | MARKDAHL, J., PROVERBIO, D., Mi, L., & GONCALVES, J. (20 August 2021). Almost global convergence to practical synchronization in the generalized Kuramoto model on networks over the n-sphere. Communications Physics, 4. doi:10.1038/s42005-021-00689-y Peer Reviewed verified by ORBi |
 | KEMP, F., PROVERBIO, D., AALTO, A., MOMBAERTS, L., FOUQUIER D'HEROUËL, A., HUSCH, A., Ley, C., GONCALVES, J., SKUPIN, A., & MAGNI, S. (2021). Modelling COVID-19 dynamics and potential for herd immunity by vaccination in Austria, Luxembourg and Sweden. Journal of Theoretical Biology. doi:10.1016/J.JTBI.2021.110874 Peer reviewed |
 | PROVERBIO, D., KEMP, F., MAGNI, S., HUSCH, A., AALTO, A., MOMBAERTS, L., SKUPIN, A., GONCALVES, J., Ameijeiras-Alonso, J., & Ley, C. (2021). Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks. PLoS ONE, 16 (5), 0252019. doi:10.1371/journal.pone.0252019 Peer Reviewed verified by ORBi |
 | PROVERBIO, D., Gallo, L., Passalacqua, B., Pellegrino, J., & Maggiora, M. (05 November 2020). Assessing the robustness of decentralized gathering: a multi‐agent approach on micro‐biological systems. Swarm Intelligence, 14, 313–331. doi:10.1007/s11721-020-00186-y Peer reviewed |
 | BANIASADI, M., PROVERBIO, D., GONCALVES, J., HERTEL, F., & HUSCH, A. (2020). FastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields. NeuroImage. doi:10.1016/j.neuroimage.2020.117330 Peer Reviewed verified by ORBi |
 | PROVERBIO, D., KEMP, F., MAGNI, S., HUSCH, A., AALTO, A., MOMBAERTS, L., GONCALVES, J., SKUPIN, A., Ameijeiras-Alonso, J., & Ley, C. (2020). Assessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/44206. doi:10.1101/2020.04.22.20075804doi: |
 | MARKDAHL, J., PROVERBIO, D., & GONCALVES, J. (2020). Robust synchronization of heterogeneous robot swarms on the sphere. In 2020 59th IEEE Conference on Decision and Control (CDC). IEEE. doi:10.1109/CDC42340.2020.9304268 Peer reviewed |
 | PROVERBIO, D., & Maggiora, M. (2019). Dynamical strategies for obstacle avoidance during Dictyostelium discoideum aggregation: a Multi-agent system model. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/39943. |
 | PROVERBIO, D., & HUSCH, A. (2019). ApproXON: Heuristic Approximation to the E-Field-Threshold for Deep Brain Stimulation Volume-of-Tissue-Activated Estimation. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/41183. doi:10.1101/863613 |