I am a geographer interested in exploring tourism system dynamics and assessing tourism’s role in environmental sustainability using agent-based modelling (ABM). My current work focus is on human complex systems interactions with the environment and on the application of tools (such as scenario analysis, network analysis and ABM) to explore topics systems adaptation, vulnerability and resilience to global change. I am also interested in looking into my PhD future research directions which pointed the potential of Big Data, social media and Volunteer Geographical Information to increase destination awareness.
I have extensive experience in GIS, quantitative and qualitative methods of research. My master thesis assessed the potential for automatic feature extraction from QuickBird imagery for municipal management purposes. During my PhD I have published and submitted several scientific papers in ISI indexed journals. I have a good research network in Portugal and I integrate an international research network on the topic “ABM meets tourism”. I am a collaborator in a recently awarded USA NCRCRD grant project “Using Agent Based Modelling to Understand and Enhance Rural Tourism Industry Collaboration” and applied for NSF funding with the project “Understanding and Enhancing the Resilience of Recreation and Tourism Dependent Communities in the Gulf”.

The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.

The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.

My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.

My main research areas are agent-based modelling, urban analytics and complex decision making enabled by AI. I am interested in the bottom-up transition of complex urban systems under major socio-economic and environmental shocks, such as climate change and the fourth industrial revolution. I want to understand how cities as self-organised complex systems respond to external shocks and evolve under a constantly changing environment. In the past, I have looked at various aspects of urban systems, including the housing market, the labour market, transport and energy system. I am also interested in decision making in complex systems. For example, I have studied the decision to become a vegetarian/vegan under social influence. I have also looked at global food trade in a complex trade network and the resulting food and nutrition security. Recently, I am interested in applying AI algorithms especially reinforcement learning in multi-agent systems, including applications of AI in urban adaptation to climate change, housing market dynamics and criminal behaviour in an urban system.