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.

Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.

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.