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Science is most interesting when it subverts expectations. As a medic in the army, I used to think of the world in terms of strict hierarchies; some central governing agency gives orders, which trickle down the chain of command. However, it turns out that most biological systems do not work this way, instead distributing control among the members of the group (be they genes, cells, animals). I have since dedicated my research career to understanding how this works. Currently, I am a postdoctoral fellow at Arizona State University in the School of Complex Adaptive Systems, which is the same university where I received my PhD.
I am broadly interested in using both experimental and theoretical tools to uncover the cognitive mechanisms that underlie self-organization in complex adaptive systems. I am also interested in the optimal design of experiments for the biological sciences.
I have a particular interest in the way in which social network structure influences dynamic processes operating over the netowrk, such as adoption of behaviour or spread of disease. More generally, I am interested in using complex systems methods to understand social phenomena.
I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.
I live in Salento, a small land located between two seas in Southeastern Italy. I work as an educator in an adult school. My educational background includes a degree in Life Sciences. During my post-graduate training, I was involved in researching the genetic and molecular responses of cells to environmental and genomic stresses. Currently, I am interested in exploring theoretical biology and complex adaptive systems through agent-based modelling.
Artificial Life, Adaptive Cognition, Evolvability
Interested in numerical models and new conceptual ideas, applications from industry to medicine.
I focus on numerical modeling of mechanics of solid materials and cell mechanics. The models that I developed so far address granular matters, bio-fluids, cellular tissues, and individual cells.
I further develop Agent-based Models, which are methods to predict collective behavior from individual dynamics controlled by rules or differential equations. Examples: tumor growth, swarms, crowd movement.
The methods I used are Particle-based methods which offer great flexibility within physical modeling, and can operate in a large range of scales, from atomistic scales (e.g. Molecular Dynamics) to continuum approaches (e.g. Smoothed Particle Hydrodynamics).
Guido Fioretti, born 1964, graduated in Electronic Engineering in 1991 at La Sapienza University, Rome. In 1995, he received a PhD in Economics from this same university. Guido Fioretti is currently a lecturer of Organization Science at the University of Bologna.
I am interested in combining social with cognitive sciences in order to model decision-making facing uncertainty. I am particularly interested in connectionist models of individual and organizational decision-making.
I may make use of agent-based models, statistical network analysis, neural networks, evidence theory, cognitive maps as well as qualitative research, with no preference for any particular method. I dislike theoretical equilibrium models and empirical research based on testing obvious hypotheses.
Researcher at LASTIG lab (https://www.umr-lastig.fr)
Agent based modeling and simulation for social sciences
Model exploration
I am an agent-based modeller at the James Hutton Institute in Scotland. I specialise in large-scale modelling of social and socio-ecological systems, with a particular focus on simulating stressors and process that could give rise to transformational change. To date, my research has focused on food and agricultural systems, rural economies, and the WASH sector, with much of it informed by firsthand fieldwork in Africa, Asia, and Europe. I am also interested in leveraging open science, participatory research, quantitative ethnography, and grounded theory within modelling processes to collaboratively generate nuanced insights into individual behaviour and societal dynamics. I received the Open Science Award from the International Land Use Study Centre in 2023 for such work. I currently co-lead the European Social Simulation Association’s Special Interest Group on Modelling Transformative Change.
I am Colombian with passion for social impact. I believe that change starts at the individual, community, local and then global level. I have set my goal in making a better experience to whatever challenges I encounter and monetary systems and governance models is what concerns me at the time.
In my path to understanding and reflecting about these issues I have found my way through “Reflexive Modeling”. Models are just limited abstractions of reality and is part of our job as researchers to dig in the stories behind our models and learn to engage in a dialogue between both worlds.
Technology empowers us to act locally, autonomously and in decentralized ways and my research objective is to, in a global context, find ways to govern, communicate and scale the impact of alternative monetary models. This with a special focus on achieving a more inclusive and community owned financial system.
As a Ph.D. fellow for the Agenda 2030 Graduate School, I expect to identify challenges and conflicting elements in the sustainability agenda, contribute with new perspectives, and create solutions for the challenges ahead
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