Advanced Techniques for Modeling and Simulation of Socioeconomic and Cyber Physical Systems: Theory and Applications - with Prof. Rodrigo Castro
On November 3 at 14:00 (Aula 3), the Institute of Economics and L’EMbeDS Department of Excellence of the Sant'Anna School are organizing a seminar entitled “Advanced Techniques for Modeling and Simulation of Socioeconomic and Cyber Physical Systems: Theory and Applications” held by prof. Rodrigo Castro, University of Buenos Aires.
Remote access to the event is available via the following link
Abstract:
In an increasingly interconnected world, the grand challenges of sustainability, equity, and resilience reside at the nexus of technological infrastructure and human social dynamics.
Prof. Castro explores the methodological core of their laboratory, which operates as an interdisciplinary hub dedicated to addressing this complexity. The laboratory posits that computational modeling and simulation form an essential unifying fabric for integrating diverse fields of knowledge.
Its work is structured around a two-sided paradigm: one side focuses on the precise engineering of cyber-physical systems, while the other confronts the out-of-equilibrium nature of socioeconomic systems. What binds engineers, computer scientists, economists, and sociologists in the laboratory is a shared concern: how to leverage computational understanding to nudge reality towards fairer and more sustainable possible states.
The team employs a synergistic combination of techniques, including multi-paradigm modeling, hybrid simulation, machine learning, genetic algorithms, network science, multi-resolution (meso–micro–macro) hierarchical models, live emergent behavior detection, and non-linear dynamical systems, among others. Their work is methodologically grounded in formal principles of multi-formalism modeling (promoting composability, reusability, continuity, and correctness) and in formal simulation frameworks (enhancing performance, scalability, and portability) of the resulting algorithms.
The talk illustrates this transdisciplinary approach through a series of case studies, such as agent-based models with forecasting capabilities, AI-assisted modeling, machine learning for high-frequency nowcasting of economic activity, multi-resolution contagion dynamics in indoor spaces, economic complexity-based future scenarios for digital transformation, supervisory control of swarm dynamics, and simulation-driven robotics in the Internet of Things.
The overarching goal is to advance towards a consistent methodological framework for designing, testing, and validating policies and technologies in silico, with the aim of providing decision-makers with more effective tools to steer today’s complex socio-cyber-physical systems.
Academic positions:
Associate Professor (Department of Computer Science, FCEyN-UBA). Independent Researcher and Deputy Director (Institute of Computer Science, ICC-UBA-CONICET). Director of the Discrete Event Simulation Laboratory (SEDLab-ICC).