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.

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.

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.

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.

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.

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.