I am an Associate Professor in the Department of Geography at the University of Montreal. My research interests center around the incorporation of artificial intelligence and machine learning techniques into the development Agent-Based Models to solve complex socio-ecological problems in different kind of systems, such as urban, forest and wetland ecosystems.

The core of my research projects aim to learn more about spatial and temporal interactions and relationships driving changes in our world, by focusing on the multidisciplinary nature of geographical information science (GIScience) to investigate the relationships between ecological processes and resulting spatial patterns. I integrate spatial analysis and modeling approaches from geographic information science (GIScience) together with computational intelligence methods and complex systems approaches to provide insights into complex problems such as climate change, landscape ecology and forestry by explicitly representing phenomena in their geographic context.

Specialties: Agent-based modeling, GIScience, Complex socio-environmental systems, Forestry, Ecology

• Modeling human-plant interactions in the origin of agriculture: Multiparadigmatic modeling and simulation (ABM, System Dynamics) of the interaction between humans and plants during domestication.
• Modeling cooperation in small-scale food economies: Agent-based modeling and simulation of the mechanisms involved in the emergence and disruption of cooperative behavior and institutions.
• Models of resource metabolism: study of matter, information and energy flows in systems with living agents at all scales.
• Modeling prehistoric hunting: modeling hunting at the scale of individuals to understand the immediate constraints of hunting as an ecological, economical and social activity.
• Modeling the interaction between herding and farming in arid environments: Agent-based modeling and simulation of the mechanisms involved in the formation and change of agro-pastoral land use patterns (sedentary farming and mobile herding) in the arid Afro-Eurasia.
• Models for games, games for models: Explore the intersection between modeling in Archaeology and game design, aiming to improve our understanding of the long-term implications of human behavior.

Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,

My broad research interests are in human-environmental interactions and land-use change. Specifically, I am interested in how people make land-use decisions, how those decisions modify the functioning of natural systems, and how those modifications feedback on human well-being, livelihoods, and subsequent land-use decisions. All of my research begins with a complex systems background with the aim of understanding the dynamics of human-environment interactions and their consequences for environmental and economic sustainability. Agent-based modeling is my primary tool of choice to understand human-environment interactions, but I also frequently use other land change modeling approaches (e.g., cellular automata, system dynamics, econometrics), spatial statistics, and GIS. I also have expertise in synthesis methods (e.g., meta-analysis) for bringing together leveraging disparate forms of social and environmental data to understand how specific cases (i.e., local) of land-use change contribute to and/or differ from broader-scale (i.e. regional or global) patterns of human-environment interactions and land change outcomes.

Complex adaptive systems, sustainability, evolution, computational social science, data science, empirical computer science, industrial regeneration, artificial intelligence

My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I’ve done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.

Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.

Improving agent models and architectures for agent-based modelling and simulation applied to crisis management. In particular modelling of BDI agents, emotions, cognitive biases, social attachment, etc.

Designing serious games to increase awareness about climate change or natural disasters; to improve civil engagement in sustainable urban planning; to teach Artificial Intelligence to the general public; to explain social phenomena (voting procedures; sanitary policies; etc).

I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).

I am currently head of the Working Group POLISES which uses agent-based models to study the impact of policies on land user behavior and consequences on the social-ecological system. This includes agri-environmental schemes for European agriculture and climate related policies such as insurance. In prior projects we investigated intended and unintended effects of global policy instruments on the social-ecological resilience of smallholders. We focused on the impact of policies targeting climate risk in common property regimes of pastoralists in Africa (Morocco and Kenya/Ethiopia).
On a conceptual level, I work in an international team of modellers, psychologists, agroeconomists and natural scientists on adequate representations of human behaviour in agent-based models. Furthermore, I am interested in how to describe models in an appropriate and standardised manner to increase their comprehensibility and comparison and how to foster model reuse and building up on each others work.

The Global Resource Observatory (GRO)

The Global Resource Observatory is largest single research project being undertaken at the GSI, it investigates how the scarcity of finite resources will impact global social and political fragility in the short term. The ambitious three year project, funded by the Dawe Charitable Trust, will enable short term decision making to account for ecological and financial constraints of a finite planet.

GRO will include an open source multidimensional model able to quantify the likely short term interactions of the human economy with the carrying capacity of the planet and key scarce resources. The model will enable exploration of the complex interconnections between the resource availability and human development, and provides projections over the next 5 years.

Data and scenarios will be geographically mapped to show the current and future balance and distribution of resources across and within countries. The GRO tool will, for the first time, enable the widespread integration of the implications of depleting key resource into all levels of policy and business decision-making.