Community

Displaying 10 of 43 results for "Christian Ringle" clear search

Moira Zellner Member since: Fri, Dec 06, 2013 at 04:16 AM Full Member

PhD, Urban and Regional Planning, University of Michigan, Ann Arbor

Moira Zellner’s academic background lies at the intersection of Urban and Regional Planning, Environmental Science, and Complexity. She has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological and behavioral factors influence the emergence and impacts of a range of complex socio-ecological systems problems, where interaction effects make responsibilities, burdens, and future pathways unclear. Her research also examines how participatory complex systems modeling with stakeholders and decision-makers can support collaborative policy exploration, social learning, and system-wide transformation. Moira has taught a variety of courses and workshops on complexity-based modeling of socio-ecological systems, for training of researchers, practitioners, and decision-makers in the US and abroad. She has served the academic community spanning across the social and natural sciences, as reviewer of journals and grants and as a member of various scientific organizations. She is dedicated to serving the public through her engaged research and activism.

Applications of agent-based modeling to urban and environmental planning
Participatory modeling

Davide Natalini Member since: Sat, Dec 07, 2013 at 12:57 PM

MSc in Political Science - Environmental Policies and Economics, University of Torino, Italy, BSc in Political Science - International Relations, University of Bologna, Italy

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.

Christian Black Member since: Mon, Mar 03, 2014 at 08:44 PM

B.Sc. Environmental Chemistry

Xiaotian Wang Member since: Fri, Mar 28, 2014 at 02:23 AM

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.

Christian Luhmann Member since: Sat, Aug 02, 2014 at 08:51 PM Full Member

Elpida Tzafestas Member since: Sun, Dec 14, 2014 at 05:32 PM

Electrical and Computer Engineering Degree, DEA (MSc) in Artificial Intelligence, PhD in Artificial Intelligence

Electrical and Computer Engineer (NTU, Athens), M.Sc. and Ph.D. on Artificial Intelligence (Univ. Paris VI, France). Formerly senior researcher in the Institute of Communication and Computer Systems (NTU, Athens). I have taught a variety of courses on intelligent, complex and biological systems and cognitive science. I have participated in numerous national and european R&D projects and I have authored about a hundred articles in journals, books and conference proceedings, at least half of them as a single author. I am frequent reviewer for journals, conferences and research grants. My research interests lie on the intersection of biological, complex and cognitive systems and applications.

Area: Complex Biological, Social and Sociotechnical Systems
Specific focus: Origins of intelligent behavior

Giorgio Gosti Member since: Tue, Jan 13, 2015 at 12:50 PM

Magistral Degree, Physics, University of Rome, “La Sapienza”, Italy, Dottorato, Computer Science and Mathemaatics, University of Perugia, Italy, PhD, Institute for Mathematical Behavioral Sciences, Social Science, University of California, Irvine

My research focuses pn the intersection between game theory, social networks, and multi-agent simulations. The objectives of this scientific endeavor are to inform policy makers, generate new technological applications, and bring new insight into human and non-human social behavior. My research focus is on the transformation of cultural conventions, such as signaling and lexical forms, and on many cell models models of stem cell derived clonal colony.

Because the models I analyze are formally defined using game theory and network theory, I am able to approach them with different methods that range from stochastic process analysis to multi-agent simulations.

Vojtech Kase Member since: Fri, Feb 20, 2015 at 01:49 PM Full Member

MA

I am interested in the dynamics of cultural transmission, especially in diffusion of religious innovations (concepts and practices) across a population. In my dissertation, I am targeting this issue while studying and modelling the development of Christian meal practices in the first four centuries CE across the Roman Mediterranean.

Christine Ornetsmuller Member since: Thu, Feb 26, 2015 at 12:47 PM

Pieter Van Oel Member since: Mon, Apr 13, 2015 at 07:11 AM

PhD

I am fascinated by unraveling water-scarcity patterns. I am an expert in Integrated Assessment Modelling and Water Footprint Assessment. The concepts and tools that I have developed and applied all aim at availing knowledge at scales relevant to decision-makers in the water sector. During my PhD at the University of Twente I evaluated how spatiotemporal patterns of water availability relate to patterns of water use for a river basin in the semi-arid Northeast of Brazil. I have used agent-based modelling and developed the downstreamness concept to analyze the emergence of basin closure. This concept is helpful to water managers for identifying priority locations for intervention inside a river basin system. As a postdoc I continued to evaluate the relation between water use and availability and further broadened my scope to a wider range of related topics.

Displaying 10 of 43 results for "Christian Ringle" clear search

This website uses cookies and Google Analytics to help us track user engagement and improve our site. If you'd like to know more information about what data we collect and why, please see our data privacy policy. If you continue to use this site, you consent to our use of cookies.
Accept