Complexity science, Statistical physics, Complex multiscale stochastic systems, Agent-based modeling, Stochastic methods, Computational reproducibility, Quantum computing, Global risk, Evidence-based policy making
I obtained my PhD in Informatics at UIUC in 2020, and prior a Bachelor’s degree in computer science and engineering at the Costa Rica Institute of Technology.
I apply statistical physics methods and computational tools –i.e., agent-based modeling, stochastic processes, quantum computation- to understand strongly complex systems, where components are highly interdependent with each other at multiple scales of action. With a background in policy making and information sciences, my goal is to work with designers to translate these and other scientific findings into actionable items that benefit user communities and impact decision-making where it matters most.
Bulletin of the American Physical Society
Journal of Experimental & Theoretical Artificial Intelligence
Conference of The Computational Social Science Society of the Americas
Núñez-Corrales, S., 2022. Recovery of resonant stochastic fluctuations in an interacting-particle system-based contagion model coupled with social mimicry: comparative analysis of the effect of event ordering in their corresponding agent based models. Bulletin of the American Physical Society.
Núñez-Corrales, S. and Jakobsson, E., 2021. Entropic boundary conditions towards safe artificial superintelligence. Journal of Experimental & Theoretical Artificial Intelligence, pp.1-33.
Núñez-Corrales, S., Friesen, M., Mudigonda, S., Venkatachalapathy, R. and Graham, J., 2021. In-Silico Models With Greater Fidelity to Social Processes: Towards ABM Platforms With Realistic Concurrency. In Proceedings of the 2020 Conference of The Computational Social Science Society of the Americas (pp. 155-169). Springer, Cham.
Núñez-Corrales, S. and Jakobsson, E., 2020. The epidemiology workbench: a tool for communities to strategize in response to covid-19 and other infectious diseases. medRxiv.