Displaying 10 of 132 results for "Kam L Yeung" clear search
I am interested in questions of method, and in the application of computational social models to a wide variety of national security questions (such as counterterrorism and counterinsurgency) as well as decision-making around complex natural resources such as water. My methods interest center on the use of qualitative social theory to inform the structure of computational social models, and the ways in which such models handle qualitative data. This raises questions around the nature of data and the ways in which computational social models convey information to decision-makers.
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.
My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.
I studied Molecular Biology and Genetics at Istanbul Technical University. During my undergraduate studies I became interested in the field of Ecology and Evolution and did internships on animal behaviour in Switzerland and Ireland. I then went on to pursue a 2-year research Master’s in Evolutionary Biology (MEME) funded by the European Union. I worked on projects using computer simulations to investigate evolution of social complexity and human cooperation. I also did behavioural economics experiments on how children learn social norms by copying others. After my Master’s, I pursued my dream of doing fieldwork and investigating human societies. I did my PhD at UCL, researching cultural evolution and behavioural adaptations in Pygmy hunter-gatherers in the Congo. During my PhD, I was part of an inter-disciplinary Hunter-Gatherer Resilience team funded by the Leverhulme Trust. I obtained a postdoctoral research fellowship from British Academy after my PhD. I am currently working as a British Academy research fellow and lecturer in Evolutionary Anthropology and Evolutionary Medicine at UCL.
I work as a Senior Researcher at the Centre for Modeling Social Systems (CMSS) at the Norwegian Research Centre (NORCE) sinde 2023. Before, I worked as an Expert Research Engineer at the CEA LIST Institute, Paris-Saclay University in France from 2013 to 2023. I hold a PhD in Artificial Intelligence degree from the Paul Sabatier University (France) and a PhD in Computer Engineering degree from the Ege University (Turkey).
I work in the field of complex adaptive systems, specializing in multi-agent systems, simulation, machine learning, collective intelligence, self-organization, and self-adaptation. I am interested in contributing to innovative projects and research in these domains.
My experience spans across multiple large-scale international research projects in areas such as green urban logistics, blockchain for nuclear applications, autonomous robotics systems and simulation of biological neural networks.
I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.
My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).
As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).
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.
I am currently completing a PhD on information sharing for natural resources management. Research is based on case studies on oyster farming, in the Thau Basin, France and in New South Wales, Australia
I am interested in the study of small-group decision-making using agent-based simulation of models grounded in sociological social psychology. I am also interested in a particular kind of small-group decision-making: peer review.
Displaying 10 of 132 results for "Kam L Yeung" clear search