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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
Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.
I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.
While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.
http://learnmem.cshlp.org/content/27/1.cover-expansion
(Cover simulation using NetLogo, January 2020)
Enver Miguel Oruro, Grace V.E. Pardo, Aldo B. Lucion, Maria Elisa Calcagnotto and Marco A. P. Idiart. Maturation of pyramidal cells in anterior piriform cortex may be sufficient to explain the end of early olfactory learning in rats. Learn. Mem. 2020. 27: 20-32 © 2020 Oruro et al.; Published by Cold Spring Harbor Laboratory Press
http://learnmem.cshlp.org/content/27/12.cover-expansion
(paper using NetLogo, December 2020)
Enver Miguel Oruro, Grace V.E. Pardo, Aldo B. Lucion, Maria Elisa Calcagnotto and Marco A. P. Idiart. The maturational characteristics of the GABA input in the anterior piriform cortex may also contribute to the rapid learning of the maternal odor during the sensitive period Learn. Mem. 2020. 27: 493-502 © 2020 Oruro et al.; Published by Cold Spring Harbor Laboratory Press
Enver Oruro, BA Psych. PhD(s).
Computational Psychologist
[email protected]
https://br.linkedin.com/in/enveroruro
Neurocomputational and Language Processing Laboratory, Institute of Physics/ UFRGS
Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry/ UFRGS
Meeting Organization
2009 First Meeting on Complex Systems -Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima
2010 Second Meeting on Complex Systems - College of Psychologists of Peru / Colegio de Psicólogos del Perú (CPsP) Lima
2012 3rd Meeting on Complex Systems – Computational Social Psychology, /Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima February 2012 https://www.comses.net/events/185/
http://www.neurocienciaperu.org/home/3ra-reunion-de-sistemas-complejos-psicologia-social-computacional
2012 4th Meeting on Complex Systems – Cognotecnology and Cognitive Science, Neuroscience and Behavior Laboratory, School of Medicine UPCH Lima July 2012 https://www.comses.net/events/212/
2014 5th Meeting on Complex Systems – Complexity Roadmap. The Imperial City of the Incas, Cusco, April. https://www.comses.net/events/312/
2015 Chair of “e-session on Neuroscience and Behavior” UNESCO UniTwin CS-DC’15
2015 Chair of “e-session on Social Psychology” UNESCO UniTwin CS-DC’15
CS-DC’15 (Complex Systems Digital Campus ’15 – World e-Conference) is organizing the e-satellites of CCS’15, the international Conference on Complex Systems. It is devoted to all scientists involved in the transdisciplinary challenges of complex systems, crossing theoretical questions with experimental observations of multi-level dynamics. CCS’15 is organized by the brand new ASU-SFI Center for Biosocial Complex Systems. Arizona State University, (USA) from Sept 28 to Oct 2, 2015, in close collaboration with the Complex Systems Society and the Santa Fe Institute. from http://cs-dc-15.org/
2018 Seminar in “Mother-Infant Attachment and Supercomputing”, NY. USA and Porto Alegre, Brazil, August 09. https://www.comses.net/events/499/
2019 Seminar in Experimental and Computational Studies on Mother-Infant Relationship October 8 and 15, 2019 ICBS, /Determine the neural pathways by which the nervous system of the neonates establish attachment with their mothers is a problem that has motivated hypothesis and experiments at several scale levels, from neurotransmission to ethological level. UFRGS, Porto Alegre, Brazil. https://www.comses.net/events/549/
2020 Seminar in Maternal Infant Relationship Studies: Neuroscience and Artificial Intelligence March 7 and 9
Goals 1. Discuss a Roadmap for mother-Infant relationship research in the framework of the UNESCO Complex System Digital Campus project. https://www.comses.net/events/570/ https://sites.google.com/view/envermiguel/seminar-in-maternal-infant-relationship-studies?read_current=1
https://drive.google.com/file/d/1-FVQXBXy4RLKIQA-RBx3KFLJxyBsnyCW/view?usp=sharing
Linea de investigacion: Estrategias de modelamiento en Psicobiologia y Psicologia Social
/ Linea estrategica 1: bases biologicas de la cognicion social desde sistemas complejos
Professor, School of Human Evolution & Social Change
Professor, School of Complex Adaptive Systems
Affiliate Professor, School of Earth and Space Exploration
Arizona State University
My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I’ve done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
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