Prof. Christian E. Vincenot is by nature an interdisciplinary researcher with broad scientific interests. He majored in Computer Science / Embedded Systems (i.e. IoT) at the Université Louis Pasteur (Strasbourg, France) while working professionally in the field of Computer Networking and Security. He then switched the focus of his work towards Computational Modelling, writing his doctoral dissertation on Hybrid Modelling in Ecology, and was awarded a PhD in Social Informatics by Kyoto University in 2011 under a scholarship by the Japanese Ministry of Research. He subsequently started a parallel line of research in Conservation Biology (esp. human-bat conflicts) under a postdoctoral fellowship of the Japanese Society for the Promotion of Science (JSPS) (2012-2014). This led him to create the Island Bat Research Group (www.batresearch.net), which he is still coordinating to this date. In 2014, he was appointed as the tenured Assistant Professor of the Biosphere Informatics Laboratory at Kyoto University. He also been occupying editorial roles for the journals PLOS ONE, Frontiers in Environmental Science, and Biology. In 2020, he created Ariana Technologies (www.ariana-tech.com), a start-up operating in the field of Data Science/Simulation and IoT for crisis management.
Prof. Vincenot’s main research interests lie in the theoretical development of Hybrid Mechanistic Simulation approaches based on Individual/Agent-Based Modeling and System Dynamics, and in their applications to a broad range of systems, with particular focus on Ecology.
Volker Grimm currently works at the Department of Ecological Modelling, Helmholtz-Zentrum für Umweltforschung. Volker does research in ecology and biodiversity research.
How to model it: Ecological models, in particular simulation models, often seem to be formulated ad hoc and only poorly analysed. I am therefore interested in strategies and methods for making ecological modelling more coherent and efficient. The ultimate aim is to develop preditive models that provide mechanstic understanding of ecological systems and that are transparent and structurally realistic enough to support environmental decision making.
Pattern-oriented modelling: This is a general strategy of using multiple patterns observed in real systems as multiple criteria for chosing model structure, selecting among alternative submodels, and inversely determining entire sets of unknown model parameters.
Individual-based and agent-based modelling: For many, if not most, ecological questions individual-level aspects can be decisive for explaining system-level behavior. IBM/ABMs allow to represent individual heterogeneity, local interactions, and/or adaptive behaviour
Ecological theory and concepts: I am particularly interested in exploring stability properties like resilience and persistence.
Modelling for ecological applications: Pattern-oriented modelling allows to develop structurally realistic models, which can be used to support decision making and the management of biodiversity and natural resources. Currently, I am involved in the EU project CREAM, where a suite of population models is developed for pesticide risk assessment.
Standards for model communication and formulation: In 2006, we published a general protocol for describing individual- and agent-based models, called the ODD protocol (Overview, Design concepts, details). ODD turned out to be more useful (and needed) than we expected.
Dr. William G. Kennedy, “Bill,” is continuing to learn in a third career, this time as an academic, a computational social scientist.
His first a career was in military service as a Naval Officer, starting with the Naval Academy, Naval PostGraduate School (as the first computer science student from the Naval Academy), and serving during the Cold War as part of the successful submarine-based nuclear deterrent. After six years of active duty service, he served over two decades in the Naval Reserves commanding three submarine and submarine-related reserve units and retiring after 30 years as a Navy Captain with several personal honors and awards.
His second career was in civilian public service: 10 years at the Nuclear Regulatory Commission and 15 years with the Department of Energy. At the NRC he rose to be an advisor to the Executive Director for Operations and the authority on issues concerning the reliance on human operators for reactor safety, participating in two fly-away accident response teams. He left the NRC for a promotion and to lead, as technical director, the entrepreneurial effort to explore the use of light-water and accelerator technologies for the production of nuclear weapons materials. That work led to him becoming the senior policy officer responsible for strategic planning and Departmental performance commitments, leading development of the first several DOE strategic plans and formal performance agreements between the Secretary of Energy and the President.
Upon completion of doctoral research in Artificial Intelligence outside of his DOE work, he began his third career as a scientist. That started with a fully funded, three-year post-doctoral research position in cognitive robotics at the Naval Research Laboratory sponsored by the National Academy of Science and expanding his AI background with research in experimental Cognitive Science. Upon completion, he joined the Center for Social Complexity, part of the Krasnow Institute for Advanced Study at George Mason University in 2008 where he is now the Senior Scientific Advisor. His research interests range from cognition at the individual level to models of millions of agents representing individual people. He is currently leading a multi-year project to characterize the reaction of the population of a mega-city to a nuclear WMD (weapon of mass destruction) event.
Dr. Kennedy holds a B.S. in mathematics from the U.S. Naval Academy, and Master of Science in Computer Science from the Naval PostGraduate School, and a Ph.D. in Information Technology from George Mason University and has a current security clearance. Dr. Kennedy is a member of Sigma Xi, the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), and a life member of Institute of Electrical and Electronics Engineers. He is a STEM volunteer with the Senior Scientists and Engineers/AAAS Volunteer Program for K-12 science, technology, engineering, and mathematics education in the DC-area schools.
Cognitive Science, Computational Social Science, Social Cognition, Autonomy, Cognitive Robotics
Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).
The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.
Name: Dr. Julia Kasmire
Position: Post-doctoral Research Fellow
Where: UK Data Services and Cathie Marsh Institute at the University of Manchester.
2004 - BA in Linguistics from the University of California in Santa Cruz, including college honours, departmental honours and one year of study at the University of Barcelona.
2008 - MSc in the Evolution of Language and Cognition from the University of Edinburgh, with a thesis on the effects of various common simulated population features used when modelling language learning agents.
2015 - PhD from Faculty of Technology, Policy and Management at the Delft University of Technology under the supervision of Prof. dr. ig. Margot Wijnen, Prof. dr. ig. Gerard P.J. Dijkema, and Dr. ig. Igor Nikolic. My PhD thesis and propositions can be found online, as are my publications and PhD research projects (most of which addressed how to study transitions to sustainability in the Dutch horticultural sector from a computational social science and complex adaptive systems perspective).
Many of the NetLogo models I that built or used can be found here on my CoMSES/OpenABM pages.
My ResearchGate profile and my Academia.org profile provide additional context and outputs of my work, including some data sets, analytical resources and research skills endorsements.
My LinkedIn profile contains additional insights into my education and experience as well as skills and knowledge endorsements.
I try to use Twitter to share what is happening with my research and to keep abreast of interesting discussions on complexity, chaos, artificial intelligence, evolution and some other research topics of interest.
You can find my SCOPUS profile and my ORCID profile as well.
Complex adaptive systems, sustainability, evolution, computational social science, data science, empirical computer science, industrial regeneration, artificial intelligence
(a) Professional Preparation
Brigham Young University Statistics & Computer Science B.S. 1986
University of North Carolina Chapel Hill Biostatistics M.S. 1988
North Carolina State University Biomathematics & Entomology Ph.D. 1997
Associate Professor 2006-current: Brigham Young University Department of Biology
Assistant Professor 2000-2006: Brigham Young University Department of Integrative Biology
Research Scientist 1997-1999: Agriculture Research Service-USDA Pacific Basin Agricultural Research Center.
i. Five most relevant publications
Ahmadou H. Dicko, Renaud Lancelot, Momar Talla Seck, Laure Guerrini, Baba Sall, Mbargou Low, Marc J.B. Vreysen, Thierry Lefrançois, Fonta Williams, Steven L. Peck, and Jérémy Bouyer. 2014. Using species distribution models to optimize vector control: the tsetse eradication campaign in Senegal. Proceedings of the National Academy of Science. 11 (28) : 10149-10154
Peck, S. L. 2014. Perspectives on why digital ecologies matter: Combining population genetics and ecologically informed agent-based models with GIS for managing dipteran livestock pests. Acta Tropica. 138S (2014) S22–S25
Peck, S. L. and Jérémy Bouyer. 2012. Mathematical modeling, spatial complexity, and critical decisions in tsetse control. Journal of Economic Entomology 105(5): 1477—1486.
Peck, S. L. 2012. Networks of habitat patches in tsetse fly control: implications of metapopulation structure on assessing local extinction probabilities. Ecological Modelling 246: 99–102.
Peck, S. L. 2012. Agent-based models as fictive instantiations of ecological processes.” Philosophy & Theory in Biology. Vol. 4.e303 (2012): 12
ii. Five other publications of note
Peck, S. L. 2008. The Hermeneutics of Ecological Simulation. Biology and Philosophy 23:383-402.
K.M. Froerer, S.L. Peck, G.T. McQuate, R.I. Vargas, E.B. Jang, and D.O. McInnis. 2010. Long distance movement of Bactrocera dorsalis (Diptera: Tephritidae) in Puna, Hawaii: How far can they go? American Entomologist 56(2): 88-94
Peck, S. L. 2004. Simulation as experiment: a philosophical reassessment for biological modeling. Trends in Ecology and Evolution 19 (10): 530 534
Storer N.P., S. L. Peck, F. Gould, J. W. Van Duyn and G. G. Kennedy. 2003 Sensitivity analysis of a spatially-explicit stochastic simulation model of the evolution of resistance in Helicoverpa zea (Lepidoptera: Noctuidae) to Bt transgenic corn and cotton. Economic Entomology. 96(1): 173-187
Peck, S. L., F. Gould, and S. Ellner. 1999. The spread of resistance in spatially extended systems of transgenic cotton: Implications for the management of Heliothis virescens (Lepidoptera: Noctuidae). Economic Entomology 92:1-16.