Behavioural ecology and modelling of ant behaviour, with an emphasis on understanding how individual-level complexity affects collective decision-making
Ecological modeller; behaviour of pollinating insects (especially bumblebees) in GIS landscapes. Hope to apply ABM methods to model some of the field data we have collected
Research focuses on the coupled dynamics of human and natural systems, specifically in the context of forest dynamics. I utilize a variety of modeling and analysis techniques, including agent-based modeling, cellular automata, machine learning and various spatial statistics and GIS-related methods. I am currently involved in projects that investigate the anthropogenic and biological drivers behind native and invasive forest pathogens and insects.
Antônio Sousa is a biologist with a background in medical entomology, disease ecology, statistical and computational modeling. Antônio has a Ph.D. (2018) and Master (2014) in Science from the School of Public Health at the University of São Paulo, Brazil. Currently, he is a postdoctoral fellow in the same institution.
My research interest lies in the study of the transmission and dispersal dynamics of vector-borne diseases. I have been working on the development of statistical, mathematical and computational models to understand bioecology of mosquitoes and to predict the transmission dynamics of pathogens transmitted by these insects.
I am strongly interested in ecological modeling and complex system and truly enjoyed working with a variety of tools to uncover patterns in empirical data and explore their ecological and evolutionary consequences. My primary research is to conduct research in the field of ‘ecological complexity’, including the development of appropriate descriptive measure to quantify the structural, spatial and temporal complexity of ecosystem and the identification of the mechanism that generate this complexity, through modeling and field studies.
Currently investigated is how biological characteristics of invasive species (dispersal strategies and demographic processes) interact with abiotic variables and resource distribution to determine establishment success and spread in a complex heterogeneous environment (Individual based modelling integrated with GIS technologies).
Social Innovation and Monetary Innovation. Developing Social Finance tools for social enterprises.
My current interests include: agent-based modeling, simulating social complexity, land use, dynamic networks, social and cultural anthropology, HIV transmission dynamics, socio-political conflicts and social movements
My research focuses on using generic social science in creating models of social reality, in particular self-organization of social systems.
PhD student at University of Toronto: memes, social networks, contagion, agent based modeling, synthetic populations
My main research interests are agent-based modeling, simulation of social complexity, computational social choice, distributed systems and applied artificial intelligence.