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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 Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge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.
Biographical Sketch
(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
(b) Appointments
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.
(c) Publications
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.
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