Displaying 10 of 43 results for "Colby Long" clear search
My research focuses on pastoral systems. I examine how pastoralists adapt to changing ecological, political and institutional conditions that affect their lives and livelihoods. I have been conducting research with pastoralists in the Far North Region of Cameroon since 1993. The long-term research has allowed me to develop innovative, interdisciplinary research projects with colleagues at the Ohio State University and the University of Maroua in Cameroon. Check out my website for more information about my research, teaching, and other scholarly activities: http://mlab.osu.edu
Pastoral systems, management of common-pool resources, coupled human and natural systems, complex adaptive systems, regime shifts, resilience, ecology of infectious diseases, herder-farmer conflicts, pastoral development, political ecology.
Amin is a PhD student in the quantitative and systems biology graduate program at UC Merced. He has been passionate about entrepreneurship since his undergraduate years in his hometown of Isfahan and then later in Bologna, Italy, where he completed his masters. Once a recipient of the Innovators Under 35 Award in Italy, he believes there is massive opportunity for society to train and motivate younger minds to acquire an entrepreneurial mindset, along with entrepreneurship skills.
Entrepreneurship, management, mathematical modeling, agent based modeling.
Experienced Water Resources Specialist with a demonstrated history of research and management. Skilled in Remote Sensing Applications, Hydrology, Spatial Analysis, and Groundwater.
Strong community and social services professional with a Master’s degree focused in Water Resources Eng. from Tarbiat Modares University. Nowadays I’m studying in Water Resources Department, University of Isfahan. Iran.
• Hydrological Modeling
• Water Resources Planning and Management
• Application of Remote Sensing in Water Resources
Peter Gerbrands is a Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure FIRMBACKBONE. He teaches data science courses and econometrics as well as supervising bachelor, master, and Ph.D. theses. 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 the Fall of 2023, he was 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
An ambitious and driven individual with knowledge and project experience in computer networks and security (BEng (Hons)), along with a masters degree at a top 10 UK university in the domain of IT, management and organizational change with a distinction, and is currently working as a Ph.D. Research fellow in Denmark.
Current Ph.D. Project - Work Improvisation, looking into more flexible and plastic management through cognition.
Organizational Cognition
Organizational behaviour
Organizational change
Gamification
Fit
Recruitment & Selection
Distribted Cognition
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.
Primate evolutionary biologist and geneticist at the University of Texas at Austin
I conduct long-term behavioral and ecological field research on several species in the primate community of Amazonian Ecuador to investigate the ways in which ecological conditions (such as the abundance and distribution of food resources) and the strategies of conspecifics together shape primate behavior and social relationships and ultimately determine the kinds of societies we see primates living in. This is a crucial and central focus in evolutionary anthropology, as understanding the ways in which behavior and social systems are shaped by environmental pressures is a fundamental part of the discipline.
I complement my field studies with molecular genetic laboratory work and agent-based simulation modeling in order to address issues that are typically difficult to explore through observational studies alone, including questions about dispersal behavior, gene flow, mating patterns, population structure, and the fitness consequences of individual behavior. In collaboration with colleagues, I have also started using molecular techniques to investigate a number of broader questions concerning the evolutionary history, social systems, and ecological roles of various New World primates.
I am a computational archaeologist and Professor of Anthropology at San Diego State University, where I direct the Computational Archaeology Laboratory. My research integrates geospatial analysis, agent-based and simulation modeling, and complex adaptive systems theory to investigate long-term human–environment interactions, with particular attention to socio-environmental change associated with early farming and herding in Mediterranean and other semi-arid landscapes. I have conducted field and modeling research in regions including Italy, Jordan, and Central Asia, and my work spans landscape archaeology, land-use dynamics, and environmental modeling. I have been a member of the CoMSES community for well over a decade and have contributed multiple models to the Computational Model Library, several of which have undergone formal peer review. In addition to research, I regularly teach with agent-based models at undergraduate and graduate levels and use CoMSES models as both research and pedagogical resources. I am committed to open, reproducible, and theoretically informed computational modeling and to strengthening the role of peer-reviewed models as durable scholarly contributions.
Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean
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}).
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.
Displaying 10 of 43 results for "Colby Long" clear search