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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
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.
In my research I focus on understanding human behaviour in group(s) as a part of a complex (social) system. My research can be characterised by the overall question: ‘How does group or collective behaviour arise or change given its social and physical context?‘ More specifically, I have engaged with: ‘How is (individual) human behaviour affected by being in a crowd?’, ‘Why do some groups (cooperatively) use their resources sustainably, whereas others do not?‘, ‘What is the role of (often implicit simplistic) assumptions regarding human behaviour for science and/or management?’
To address these questions, I use computational simulations to integrate and reflect synthesised knowledge from literature, empirics and experts. Models, simulation and data analysis are my tools for gaining a deeper understanding of the mechanisms underlying such systems. More specifically, I work with agent-based modelling (ABM), simulation experiments and data analysis of large datasets. Apart from crowd modelling and social-ecological modelling, I also develop methodological tools to analyse social simulation data and combining ABM with other methods, such as behavioural experiments.
Moira Zellner’s academic background lies at the intersection of Urban and Regional Planning, Environmental Science, and Complexity. She has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological and behavioral factors influence the emergence and impacts of a range of complex socio-ecological systems problems, where interaction effects make responsibilities, burdens, and future pathways unclear. Her research also examines how participatory complex systems modeling with stakeholders and decision-makers can support collaborative policy exploration, social learning, and system-wide transformation. Moira has taught a variety of courses and workshops on complexity-based modeling of socio-ecological systems, for training of researchers, practitioners, and decision-makers in the US and abroad. She has served the academic community spanning across the social and natural sciences, as reviewer of journals and grants and as a member of various scientific organizations. She is dedicated to serving the public through her engaged research and activism.
Applications of agent-based modeling to urban and environmental planning
Participatory modeling
Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. 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 Fall 2023, he is 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
Dr. Kimberly G. Rogers studies the coupled human-natural processes shaping coastal environments. She obtained a B.Sc. in Geological Sciences from the University of Texas at Austin and began her graduate studies on Long Island at Stony Brook University’s School of Marine and Atmospheric Sciences. Rogers completed her Ph.D. at Vanderbilt University, where she specialized in nearshore and coastal sediment transport. She was a postdoctoral scholar and research associate at the Institute for Arctic and Alpine Research at the University of Colorado Boulder. In 2014, her foundation in the physical sciences was augmented by training in Environmental Anthropology at Indiana University Bloomington through an NSF Science, Engineering, and Education for Sustainability (SEES) Fellowship.
Rogers’s research is broadly interdisciplinary and examines evolving sediment dynamics at the land-sea boundary, principally within the rapidly developing river deltas of South Asia. As deltas are some of the most densely populated coastal regions on earth, she incorporates social science methods to examine how institutions — particularly those governing land use and built infrastructure — influence the flow of water and sediment in coastal areas. She integrates quantitative and qualitative approaches in her work, such as direct measurement and geochemical fingerprinting of sediment transport phenomena, agent-based modeling, institutional and geospatial analyses, and ethnographic survey techniques. Risk holder collaboration is an integral part of her research philosophy and she is committed to co-production and capacity building in her projects. Her work has gained recognition from policy influencers such as the World Bank, USAID, and the US Embassy Bangladesh and has been featured in popular media outlets such as Slate and Environmental Health Perspectives.
My core research interest is to understand how humans and other living creature perceive and behave; respond and act upon their environment and how this dynamic interplay shapes us into who we are. In recognition of the broad scope of this question I am a strong believer in the need for inter- and multi-disciplinary approaches and have worked at research groups in a wide range of departments and institutions, including university departments of Physics as well as Psychology, a bio-medical research lab, a robotics research laboratory and most recently the RIKEN Brain Science Institute. Though my work has primarily taken the form of computational neuroscience I have also performed psychophysical experiments with healthy human subjects, been involved in neural imaging experiments and contributed towards the development of a humanoid robot.
Based on the philosophy of ‘understanding through creating’ I believe that bio-mimetic and biologically inspired computational and robotic engineering can teach us not only how to build more flexible and robust tools but also how actual living creatures deal with their environment. I am therefore a strong believer in the fertile information exchange between scientific as well as engineering research disciplines.
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.
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.
Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.
Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory
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