Displaying 10 of 282 results for "Clint A Penick" clear search
Social research - Anthropologist - Simulation of a public counter
Psychology, Opinion Dynamics, Contested Infrastructures, Social Judgment Theory
I received a PhD in Ecology from Duke University in 2006. I have been a faculty member in the Department of Biological Sciences at University of Illinois Chicago since 2008
urban ecology, socio-ecological systems, human-environment interactions, landscape ecology
Elizabeth Hunter received a BA in Mathematics and Economics at Boston University in 2011. She worked as a health economics researcher at Research Triangle Institute for three years where she worked on a team that developed the risk adjustment models for the US health insurance exchanges. She attended the University of Limerick and received an MSc in Mathematical Modelling in 2015. She completed a PhD at Technological University Dublin. Her PhD research focuses on agent-based simulations for infectious disease epidemiology with the goal of creating an agent-based simulation of Ireland. Elizabeth is currently working on the Precise4Q as a Postdoctoral researcher working on predictive modelling in stroke.
Farzaneh Davari is a social science researcher who has worked in many diverse fields, including agriculture, conflict, health, and human rights, just to name a few. Currently, she is a Ph.D. candidate in Computational Social Science, focusing on social-ecological complex systems and applying computational science and Agent-Based Modeling to understand resilience procedure through self-organizing and learning. Meanwhile, she is a designer and instructor of the online graduate level course of Decision-making in Complex Environments in Virginia Tech.
Social-ecological complex system, resilience-building, conflictual environment
Corinna is a lecturer in the Department of Sociology. She joined the Centre for Research in Social Simulation at the in August 2008 as a Research Fellow. Her academic background is in Philosophy (LSE, BSc MSc) and Computer Science (KCL,PhD), where her PhD Instinct for Detection developed a logic for abductive reasoning.
Currently Corinna is the PI on an AHRC Research Grant on collective reasoning in agent-based modelling, titled Collective Reasoning as a Moral Point of View. Her research interests are decision mechanisms, in particular collective decision-making, context dependency of decisions and methodological and epistemological aspects of agent-based modelling and social simulation. She has applied collective decision making to the analysis to the weakening of the Mafia in Southern Italy within the GLODERS project and published a book Modelling Norms, co-authored with Nigel Gilbert, providing a systematic analysis of the contribution of agent-based modelling to the study of social norms and deviant behaviour. Recently Corinna has been developing a teaching stream within CRESS with a periodically running short course Agent-based Modelling for the Social Scientist and the MSc Social Science and Complexity.
Currently doing a program evaluation of a GIZ reforestation project in the north of Mato Grosso state, Brazil (transition area from savannah to Amazon forest). Adoption of Agroforestry Systems by lower income farmers was the goal.
The main research area is operation research in logistics with a focus on logistic cluster development and innovative technology usage. Due to mathematical background, Gružauskas focuses on quantitative analysis by conducting simulations, stochastic and dynamic models and other analytical approaches to amplify the developed theories. Gružauskas also is working as a freelance data analyst with a focus on statistical analysis, web scraping and machine learning.
I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.
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