Displaying 10 of 71 results system clear
Ms. Stringfellow is a PhD candidate whose goal is to identify ways to build and leverage the natural support systems of people who are experiencing problems related to their illicit drug use. Her current interest is in how these support systems operate in small towns with limited formal resources for quitting. To that end, she recently began conducting in-depth qualitative interviews for her dissertation in a semi-rural county in eastern Missouri. These interviews will be used to build an agent-based model, a type of dynamic simulation modeling that can be used to represent heterogeneous actors with multiple goals and perceptions. As a research assistant and dissertation fellow with the Social System Design Lab, she has also been trained in system dynamics, an aggregate-level dynamic simulation modeling method.
Prior to joining the PhD program, she worked as a research associate at the Boston Health Care for the Homeless Program from 2008-2012. BHCHP is an exemplar model of providing patient-centered care for people who have experienced homelessness. There, she gained significant experience in managing research projects, collecting qualitative and quantitative data, and program evaluation. She earned her MSW from the University of Michigan in 2007, with a focus on policy and evaluation in community and social systems, and a BA in sociology in 2005, also at the University of Michigan. Ms. Stringfellow was born and raised in a small town in Michigan.
Dr. Mariam Kiran is a Research Scientist at LBNL, with roles at ESnet and Computational Research Division. Her current research focuses on deep reinforcement learning techniques and multi-agent applications to optimize control of system architectures such as HPC grids, high-speed networks and Cloud infrastructures.. Her work involves optimization of QoS, performance using parallelization algorithms and software engineering principles to solve complex data intensive problems such as large-scale complex decision-making. Over the years, she has been working with biologists, economists, social scientists, building tools and performing optimization of architectures for multiple problems in their domain.
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 discovered at the same time Agent-Based Modeling method and Companion Modelling approach during my master degrees (engeenering and artificial intelligence and decision) internship at CIRAD in 2005 and 2006 where I had the opportunity to participate as a modeller to a ComMod process (Farolfi et al., 2010).
Then, during my PhD in computer Science applied to Modeling and Simulation, I learned the Theory of Modeling and Simulation and the Discrete EVent System specification formalism and proposed a conceptual, formal and operational framework to evaluate simulation models based on the way models are used instead of their ability to reproduce the target system behavior (Bonté et al., 2012). Applied to the surveillance of Epidemics, this work was rather theoritical but very educative and structuring to formulate my further models and research questions about modeling and simulation.
From 2011 to 2013, I worked on viability theory applied to forest management at the Compex System Lab of Irstea (now Inrae) and learned about the interest of agregated models for analytical results (Bonté et al, 2012; Mathias et al, 2015).
Since 2013, I’m working for Inrae at the joint The Joint Research Unit “Water Management, Actors, Territories” (UMR G-EAU) where I’m involved in highly engaging interdisciplinary researches such as:
- The Multi-plateforme International Summer School about Agent Based Modelling and Simulation (MISSABMS)
- The development of the CORMAS (COmmon Pool Resources Multi-Agents Systems) agent-based modeling and simulation Platform (Bommel et al., 2019)
- Impacts of the adaptation to global changes using computerised serious games (Bonté et al., 2019; Bonté et al. , 2021)
- The use of experimentation to study social behaviors (Bonté et al. 2019b)
- The impact of information systems in SES trajectories (Paget et al., 2019a)
- Adaptation and transformations of traditional water management and infrastructures systems (Idda et al., 2017)
- Situational multi-agent approaches for collective irrigation (Richard et al., 2019)
- Combining psyhcological and economical experiments to study relations bewteen common pool resources situations, economical behaviours and psychological attitudes.
My research is about modelling and simulation of complex systems. My work is to use, and participate to the development of, integrative tools at the formal level (based on the Discrete EVent System Specification (DEVS) formalism), at the conceptual level (based on integrative paradigms of different forms such as Multi-Agents Systems paradigm (MAS), SES framework or viability theory), and at the level of the use of modelling and simulation for collective decision making (based on the Companion Modelling approach (ComMod)). Since 2013 and my integration in the G-EAU mixt research units, my object of studies were focused on multi-scale social and ecological systems, applied to water resource management and adaptation of territories to global change and I added experimentation to my research interest, developping methods combining agent-based model and human subjects actions.
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.
Eric has graduate degrees in urban planning and policy and sociology and an undergraduate degree in biology. He has worked on multiple collaborative and interdisciplinary projects and is skilled at engaging communities and other stakeholders. He is adept at qualitative research and has earned a Certificate in Geospatial Analysis and Visualization, demonstrating proficiency in Adobe Suite, ArcGIS, agent-based modeling and system dynamics modeling. He is currently writing manuscripts for publication based on his work on motivating energy retrofit decisions, energy-related urban planning, municipal decision-making on infrastructure investments, and other work on resilience and sustainability.
Conducts urban planning and policy research on energy efficiency, environmental, and infrastructure decision making.
Muaz is a Senior Member of the IEEE and has more than 15 years of professional, teaching and research experience. Muaz has been working on Communication Systems and Networks since 1995. His BS project in 1995 was on the development of a Cordless Local Area Network. In 1996, his postgraduate project was on Wireless Connectivity of devices to Computers. In addition to his expertise as an Communications engineer, his areas of research interest are in the development of agent-based and complex network-based models of Complex Adaptive Systems. He has worked on diverse case studies ranging from Complex Communication Networks, Biological Networks, Social Networks, Ecological system modeling, Research and Scientometric modeling and simulation etc. He has also worked on designing and developing embedded systems, distributed computing, multiagent and service-oriented architectures.
Positions held today:
• Associate Professor for Geoinformatics and Ecology at the University of Salzburg (since 2017)
• UNIGIS Program Director (since 2020)
• Head of the Research Group “Spatial Simulation” (since 2013)
Major academic milestones:
• Assistant Professor, Department for Geoinformatics, University of Salzburg (2013-2017)
• Associate Faculty in the FWF Doctoral College “GIScience” (2013-2017)
• Director of Studies UNIGIS MSc distance learning programs, University of Salzburg (2012-2020)
• PhD at the University of Innsbruck on ecological modelling (2011)
• Research Assistant Austrian Academy of Sciences, GIScience Institute (2007-2011)
• Magistra in Ecology, Univ. of Innsbruck (2001) and MSc in GIS, Univ. of Edinburgh (2006)
Spatially-explicit simulation modelling of complex, ecological systems:
* the added value of spatially-explicit modelling
* Hybrid agent-based and system-dynamics modelling in ecology
* Agent-based models, Cellular Automata
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.
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.
Displaying 10 of 71 results system clear