Complex Systems, Social Modeling and Simulation
Engineering the Futures

Envrionmental Archaeology, Fire Ecology, GIS, Agent-based modeling, Geoarchaeology

I study he role of biologically-based motivations in the formation of socio-political phenomena using agent-based modelling techniques. In particular I look at how behaviour inhibition and activation, as well as interpersonal attitudes can shape the emergence of complex polities.

One of my research areas is agent-based modelling of land change in Brazil. I have worked with ABM in frontier areas of the Brazilian Amazon. I am also part of the team that develops TerraME, an OSS toolkit for ABM in cellular spaces.

I am broadly interested in using Agent-based Modelling, Microsimulation, Geosimulation or a hybrid of these approaches as methodology to investigate complex dynamics of systems in various domains. I am also interested in exploring the potential of simulation models as decision support and policy-informing tools.

I am a Ph.D. student studying the interactions between external regulations and social norms in natural resource management and international development. In particular, I am looking to use mixed methods research, including ethnographic research, field experiments, and agent-based computational models to explore the sustainability of market-based interventions and their possible perverse outcomes.

I am interested in using agent-based model to understand the behavior of financial markets

My interests lie in the intersection of economics, networks, and computation. I am currently studying labour dynamics as a process where people flow throughout the economy by moving from one firm to another. I study these flows by looking at detailed data about employment histories of each individual and every firm in entire economies. Using this information, I construct networks of firms in order to map the roads that people take throughout their careers. This allows to study labour markets at an unprecedented fine-grained level of detail. I employ agent-based computing methods to understand how economic shocks and policies alter labour flows, which eventually translate into unemployment and other related problems.

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.

My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.