Displaying 10 of 53 results complex systems clear
I have a particular interest in the way in which social network structure influences dynamic processes operating over the netowrk, such as adoption of behaviour or spread of disease. More generally, I am interested in using complex systems methods to understand social phenomena.
I am an assistant professor in the Department of Computer Science at the Hamedan University of Technology, Hamedan, IRAN. I have completed my Ph.D. in Futures Studies (foresight) as an interdisciplinary field, an intersection of social sciences and engineering. My
background comes from computer science. For my Ph.D., I decided to pursue my education in Futures Studies; the field I thought I could apply engineering principles such as requirements engineering, analytical skills, design, modeling, planning, and, test engineering to shape the
desired futures. In PhD, I started the complex systems research field and agent-based modeling with NetLogo. In addition to several publications of papers, I published a book on complex systems titled “Futures Studies in Complex Systems” which was awarded as the book of the year by the Iranian Foresight Association.
Since May 2021, I started a research collaboration with TISSS Lab at the Johannes Gutenberg University Mainz as a project coordinator, the German Research Centre for AI, Human-Centered Multimedia, and the Centre for Research in Social Simulation. The project title is “AI for Assessment” and its objective is to understand the status quo and the future options of AI-based social assessment in public service provisions to help in the creation of improved AI technology for social welfare systems.
On the executive side, I have also various experiences, including head of the department, deputy of the Technology Incubator Center, director of university’s research affairs, and head of the International Scientific Cooperation Office.
Complex Systems, Social Modeling and Simulation
Engineering the Futures
PhD in Physics
One year postdoctoral position at the Institute of Physics at the University of Puebla, Mexico
Two year postdoctoral position at the Institute of Physics, University of Mexico, Mexico.
Working since 2007 as a professor and researcher at the University of Mexico City, Mexico.
Complex systems
Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In Fall 2023, he is a Visiting Research Scholar at SUNY Binghamton in NY.
agent-based simulations
social network analysis
complex systems
big data analysis
statistical learning
computational social science
I am an anthropological archaeologist with broad interests in hunter-gatherers, lithic technology, human evolution, and complex systems theory. I am particularly interested in understanding processes of long term social, evolutionary, and adaptational change among hunter-gatherers, specifically by using approaches that combine archaeological data, ethnographic data, and computational modeling.
The big picture question driving my research is how do complex systems of interactions among individuals / agents result in emergent properties and how do those emergent properties feedback to affect individual / agent decisions. I have explored this big picture question in a number of different contexts including the evolution of cooperation, suburban sprawl, traffic patterns, financial systems, land-use and land-change in urban systems, and most recently social media. For all of these explorations, I employ the tools of complex systems, most importantly agent-based modeling.
My current research focus is on understanding the dynamics of social media, examining how concepts like information, authority, influence and trust diffuse in these new media formats. This allows us to ask questions such as who do users trust to provide them with the information that they want? Which entities have the greatest influence on social media users? How do fads and fashions arise in social media? What happens when time is critical to the diffusion process such as an in a natural disaster? I have employed agent-based modeling, machine learning, geographic information systems, and network analysis to understand and start to answer these questions.
My research uses modeling to understand complex coupled human and natural systems, and can be generally described as computational social science. I am especially interested in modeling water management systems, in both archaeological and contemporary contexts. I have previously developed a framework for modeling general archaeological complex systems, and applied this to the specific case of the Hohokam in southern Arizona. I am currently engaged in research in data mining to understand contemporary water management strategies in the U.S. southwest and in several locations in Alaska. I am also a developer for the Repast HPC toolkit, an agent-based modeling toolkit specifically for high-performance computing platforms, and maintain an interest in the philosophy of science underlying our use of models as a means to approach complex systems. I am currently serving as Communications Officer for the Computational Social Science Society of the Americas.
Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.
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,
I am a University Academic Fellow (UAF) in the School of Geography at the University of Leeds. My research areas are agent-based modelling, decision making in complex systems, AI and multi-agent systems, urban analytics and housing markets. I obtained PhD in Economics from Iowa State University under supervisor Prof. Leigh Tesfatsion in 2014. I worked as a researcher at the James Hutton Institute in Aberdeen, Scotland between 2014 and 2019. I joined the University of Leeds as a UAF of Urban Analytics in 2019. I am originally from Shanghai, China.
My main research areas are agent-based modelling, urban analytics and complex decision making enabled by AI. I am interested in the bottom-up transition of complex urban systems under major socio-economic and environmental shocks, such as climate change and the fourth industrial revolution. I want to understand how cities as self-organised complex systems respond to external shocks and evolve under a constantly changing environment. In the past, I have looked at various aspects of urban systems, including the housing market, the labour market, transport and energy system. I am also interested in decision making in complex systems. For example, I have studied the decision to become a vegetarian/vegan under social influence. I have also looked at global food trade in a complex trade network and the resulting food and nutrition security. Recently, I am interested in applying AI algorithms especially reinforcement learning in multi-agent systems, including applications of AI in urban adaptation to climate change, housing market dynamics and criminal behaviour in an urban system.
Tarik Hadzibeganovic is a complex systems researcher and cognitive scientist interested in all challenging topics of mathematical and computational modeling, in both basic and applied sciences. His particular focus has been on several open questions in evolutionary game theory, behavioral mathematical epidemiology, sociophysics, network theory, and episodic memory research. When addressing these questions, he combines mathematical, statistical, and agent-based modeling methods with laboratory behavioral experiments and Big Data analytics.
Displaying 10 of 53 results complex systems clear