Juan obtained a BSc and MSc from Universidad Miguel Hernández and a Masters in Physics and Modelling of Complex Systems from Universidad Rey Juan Carlos. He completed his PhD at Universidad Rey Juan Carlos in Nonlinear Dynamics and Chaos Theory, specializing in the development of a novel control method for chaotic systems known as Partial Control. Additionally, he worked as an Assistant Professor at Universidad Rey Juan Carlos, primarily focusing on modeling complex systems.

He was actively involved in the Systemic Risk Modelling project at the Institute for New Economic Thinking in Oxford. This project demonstrated the advantages of diverse risk models in the market. He made significant contributions to the development of one of the most advanced agent-based models ever created for the catastrophe insurance market.

He played a key role in the HESTIA project at the Oxford Martin School. In this project, he contributed to the implementation of a cloud-based platform that enables researchers worldwide to share environmental impact assessments. The platform had a specific focus on supporting sustainable food production.

During his last postdoctoral position at the Smith School of Enterprise and the Environment, he conducted asset-level research on the global beef supply chain, its environmental impact, and the role of indirect suppliers. He also led the development of the first farm asset-level dataset for the UK, allowing for the first-time estimation of environmental impacts at the farm level.


  • Ranger, N., Alvarez J., Freeman, A., Harwood, T., Obersteiner, M., Paulus, E. and Sabuco, J. (2023). The Green Scorpion: the Macro-Criticality of Nature for Finance – Foundations for scenario-based analysis of complex and cascading physical nature-related risks. Oxford: Environmental Change Institute, University of Oxford.
  • López, A.G., Benito, F., Sabuco, J., Delgado-Bonal, A. 2023. The thermodynamic efficiency of the Lorenz system. Chaos, Solitons & Fractals, 172:113521. doi: 10.1016/j.chaos.2023.113521
  • Kolic, B., Sabuco, J. and Farmer, J.D. 2022. Estimating initial conditions for dynamical systems with incomplete information. Nonlinear Dynamics, 108(4): 3783-3805. doi: 10.1007/s11071-022-07365-y
  • Heinrich, T., Sabuco, J. and Farmer, J.D. 2021. A simulation of the insurance industry: The problem of risk model homogeneity. Journal of Economic Interaction and Coordination, 17:535–576. doi: 10.1007/s11403-021-00319-4
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2019. A new approach of the partial control method in chaotic systems. Nonlinear Dynamics, 98(2):873-887. doi: 10.1007/s11071-019-05215-y
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2018. Partial control of chaos: how to avoid undesirable behaviors with small controls in presence of noise. Discrete Continuous Dynamical Systems – Series B, 23(8): 3237-3274. doi: 10.48550/arXiv.1803.09634
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2018. Partial control of delay-coordinate maps. Nonlinear Dynamics, 92:1419-1429. doi: 10.1007/s11071-018-4136-y
  • Levi, A., Sabuco, J., Small, M. and Sanjuán, M.A.F. 2018. From local uncertainty to global predictions: Making predictions on fractal basins. PLOS ONE, 13(4):e0194926. doi: 10.1371/journal.pone.0194926
  • Levi, A., Sabuco, J. and Sanjuán, M.A.F. 2017. When the firm prevents the crash: Avoiding market collapse with partial control. PLOS ONE, 12(8): e0181925. doi: 10.1371/journal.pone.0181925
  • Levi, A., Sabuco, J. and Sanjuán, M.A.F. 2017. Supply based on demand dynamical model. Communications in Nonlinear Science and Numerical Simulation, 57:402-414. doi: 10.1016/j.cnsns.2017.10.008
  • Taghawi-Nejad, D., Tanin, R.H., Del Rio Chanona, M., Carro, A., Farmer, J.D., Heinrich, T., Sabuco, J. and Straka, M.J. 2017. ABCE: A Python Library for economic agent-based modeling. In: Ciampaglia G., Mashhadi A., Yasseri T. (eds). SocInfo 2017: Social Informatics, 1:17-30. doi: 10.1007/978-3-319-67217-5_2
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2017. Escaping from a chaotic saddle in the presence of noise. International Journal of Nonlinear Dynamics and Control, 1:78-86. doi: 10.1504/IJNDC.2017.083629
  • Agarwal, V., Sabuco, J. and Balachandran, B. 2017. Safe regions with partial control of a chaotic system in the presence of Gaussian noise. International Journal of Non-Linear Mechanics, 94:3-11. doi: 10.1016/j.ijnonlinmec.2017.01.017
  • Capeáns, R., Sabuco, J., Sanjuán, M.A.F. and Yorke, J.A. 2017. Partially controlling transient chaos in the Lorenz equations. Philosophical Transactions of the Royal Society A, 375:20160211. doi: 10.1098/rsta.2016.0211
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2016. Parametric partial control of chaotic systems. Nonlinear Dynamics, 86:869-876. doi: 10.1007/s11071-016-2929-4
  • Joseph, S.K., Sabuco, J.,  Chew, L.Y. and Sanjuán, M.A.F. 2015. Effect of geometry on the classical entanglement in a chaotic optical fiber. Optics Express, 23:32191-32201. doi: 10.1364/OE.23.032191
  • Capeáns, R., Sabuco, J. and Sanjuán, M.A.F. 2014. When less is more: Partial control to avoid extinction of predators in an ecological model. Ecological Complexity, 19:1-8. doi: 10.1016/j.ecocom.2014.02.002
  • López, A.G., Sabuco, J., Seoane, J.M., Duarte, J., Januário, C. and Sanjuán, M.A.F. 2014. Avoiding healthy cells extinction in a cancer model. Journal of Theoretical Biology, 349:74-81. doi: 10.1016/j.jtbi.2014.01.040
  • Zambrano, S., Sabuco, J. and Sanjuán, M.A.F. 2014. How to minimize the control frequency to sustain transient chaos using partial control. Communications in Nonlinear Science and Numerical Simulation, 19:726-737. doi: 10.1016/j.cnsns.2013.06.016
  • Sabuco, J., Zambrano, S. and Sanjuán, M.A.F. 2013. Further progress in partial control of chaotic systems. In: Adamatzky, A. and Chen, G. [eds], Chaos, CNN, Memristors and Beyond, pages 393-403. World Scientific. doi: 10.1142/9789814434805_0031
  • Sabuco, J., Sanjuán, M.A.F. and Yorke, J.A. 2012. Dynamics of partial control. Chaos, 22:047507. doi: 10.1063/1.4754874
  • Sabuco, J., Zambrano, S., Sanjuán, M.A.F. and Yorke, J.A. 2012. Finding safety in partially controllable chaotic systems. Communications in Nonlinear Science and Numerical Simulation, 17:4274-4280. doi: 10.1016/j.cnsns.2012.02.033