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).
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.
Ecology and population dynamics of fish and wildlife populations, epidemiology, biometry
Interested in how technology innovation impacts people’s lives.
As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.
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.
See my website for details.
Professor, School of Human Evolution & Social Change
Professor, School of Complex Adaptive Systems
Affiliate Professor, School of Earth and Space Exploration
Arizona State University
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.
Agent-based computing in economics and finance
Large-scale agent-based models
Agent models calibrated by micro-data
Complex adaptive systems
Mathematical analysis of agent systems
Simulation games, systemic complexity, learning, business cycles, and discrete-event simulation, modeling sustainability challenges in urban context.