Displaying 10 of 195 results for "Michel De Garine-Wichatitsky" clear search
Postdoctoral researcher at Institute of Economics, Polish Academy of Sciences and in Macroprudential Research Division at National Bank of Poland. She graduated in Mathematics (Jagiellonian University, Poland) and in Economics (University of Alcala, Spain). In 2017 she obtained Fulbright Advanced Research Award. In the United States, she carried out research on systemic risk and complex systems. Her doctoral dissertation was about the measurement and modeling of systemic risk using simulation methods and complex systems approach (the results to be published by Palgrave Macmillan US). Previously, she gained experience on agent-based modeling while working with Juan Luis Santos on the European Commission FP 7 MOSIPS project (http://www.mosips.eu/).
Mathematics, complex systems, financial modeling, agent-based modeling, econometrics, macroprudential policies, systemic risk, cental banking
My research centers on isolating how and to what extent political institutions themselves shape policy. I use computational modeling (agent-based and simulation) to gain theoretical leverage on the issue. This approach allows me to place groups of actors with given preferences into different institutional settings in order to gauge the effect of the rules of the game on political outcomes. Most of my research examines the ways in which legislative processes affect issues of political economy, such as income redistribution.
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.
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
MY research aims to give artists better 3D references and scene reconstructions which can be directly fed into the creative pipeline. This is motivated by increasing public demand for detailed, complex 3D worlds and the resulting demand this places on world design artists.
This project lookings at developing acquisition and modelling technologies that provide more than just a visual reference: in the context of this project, visual acquisition and reconstruction methods shall be developed that provide richer, three-dimensional references, and that ultimately yield scene reconstructions that can directly be fed into the content creation pipeline. The project will focus on natural environments (as opposed to urban scenes) and may combine multi-spectral imaging, wide-baseline stereo reconstruction and semantic scene analysis to obtain approximate procedural representations of natural scenes.
Cristina Montañola Sales is an assistant professor at Institut Químic de Sarrià in Ramon Llull University, where she teaches subjects in ICT and statistics. She holds a PhD in Statistics and Operations Research and specializes in the investigation of novel quantitative methods for studying human behavior, such as agent-based models and spatio-temporal analysis. Her interdisciplinary research combines mathematics with social sciences, biomedicine and High-Performance Computing. She has studied various contexts, such as the dynamics of mobility of Gambian emigrants, demographic forecasting in South Korea, and ecological resilience of hunter-gatherers in India. Her research on tuberculosis transmissions and COVID-19 has advanced knowledge in epidemics, demographic dynamics and computational statistics. She has published articles and participated in international projects on simulation, parallel computing and global health.
validation, computer performace, epidemics, demography
Doctor and Magister in Informatics by the Girona University (Spain), Telematics Engineer and Systems Technologist by the Francisco José de Caldas University (Bogotá, Colombia), Specialist in Databases Management, and Specialist in Higher Education. Currently, associate professor and researcher at the Fundación Universitaria Konrad Lorenz (Bogotá, Colombia). Academic leader of the Konrad IA project (IA - Artificial Intelligence). Associated researcher by the science and technology Colombian ministry.
CoMSES.Net is a good community space to share knowledge regarding agent based and computational models that are built based upon a wide variety of contexts (social, political, educational, scientific, biological, etc.). Thus, the CoMSES.Net should be known in all regions around the world. Moreover, as I belong to the Spanish-speaking community, it would be very interesting to publicize what the network does in Spanish-speaking countries.
Research topics: Inmersive Technologies, Educational Technologies, Web Accessibility and Usability, Sematic Web, Artificial Intelligence.
Anna Sikora is an Associate Professor in the Computer Architecture and Operating System Department at Autonomous University of Barcelona (UAB).
She got the BS degree in computer science in 1999 from Technical University of Wroclaw (Poland). She got the MSc in computer science in 2001 and in 2004 the PhD in computer science, both from Autonomous University of Barcelona (Spain).
Since 1999 her investigation is related to parallel and distributed computing. Her current main interests are focused on high performance parallel applications, performance models, automatic performance analysis and dynamic tuning. She has been involved in programming tools for automatic and dynamic performance tuning on cluster and Grid environments, as well as in exa-scale systems.
High performance parallel computing, parallel applications, performance models, automatic performance analysis, dynamic tuning. Performance tools for automatic and dynamic performance tuning on HPC systems. Agent-based modelling systems.
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis, using mixed and integrative methods.
Recent projects include: 1) Studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) Indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
Displaying 10 of 195 results for "Michel De Garine-Wichatitsky" clear search