Displaying 6 of 46 results for "Marco Alberti" clear search
Enver Miguel Oruro Puma Member since: Tue, Mar 23, 2010 at 11:09 PM Full Member
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
Prashant Deshpande Member since: Tue, Dec 21, 2021 at 12:36 PM Full Member
Alma Mater: FT Ranked No. 10 Business Economics school.
Ranked No 1 in an engineering mathematics national level test.
Ranked No 1 in an analytics program at IIT Bombay.
B.E. Mechanical Engineering.
MTech 1st year Modelling and Simulation.
PhD 1st year Strategy Simulation at The University of Texas at Dallas.
Tuition scholarships at the Santa Fe Institute.
GMAT 730
5 years of operations research work experience.
Published and presented a poster at the The Operational Research Society, UK Annual Conference 2021 integrating strategy and applied math. Took on and resolved a longstanding problem.
Solo authored leadership article in the Analytics magazine Nov/Dec 2021 issue from INFORMS.
Solo authored theoretical optimization abstract at the ICORES 2022 Conference.
Authoring the black-tie, board room manual - The Change Management Series Volume 1 Kindle edition on Amazon March, 2022.
I am a participant at the Financial Modeling World Cup 2022.
Build spiders for scraping web data.
Agent-based computer simulation in strategy, the resource-based view in strategy, agency theory and top & middle management incentives, organizational economics, algorithmic game theory, financial friction, financial econometrics.
Dehua Gao Member since: Mon, Jan 05, 2015 at 04:37 PM Full Member
**PROFESSIONS **
Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)
**EDUCATION BACKGROUDS **
Ph. D. Degree, 09/2009 – 07/2015
School of Economics and Management, Beihang University (P. R. China)
M. A. Degree, 09/2003 – 02/2006
The Institute of Systems Engineering, Dalian University of Technology (P. R. China)
B. A. Degree, 09/1999 – 07/2003
Department of Information and Control Engineering, Zhengzhou University of Light Industry (P. R. China)
**VISITING & SUMMER SCHOOLS **
Visiting Scholar at GECS – Research Group of Experimental and Computational Sociology (March, 2017 – February, 2018)
Università degli Studi di Brescia (Italy)
Co-supervisor: Professor Flaminio Squazzoni
Summer school in ‘Agent-based modeling for social scientists’ (September 4-8, 2017)
University of Brescia, Italy
Instructors: Flaminio Squazzoni, Simone Gabbriellini, Nicolas Payette, Federico Bianchi
The Santa Fe Institute’s Massive Open Online Course: Introduction to Agent-Based Modeling (Jun 5 – September 8, 2017)
The Santa Fe Institute, Complexity Explore Web: abm.complexityexploer.org
Instructors: Bill Rand
Summer school in ‘Complex systems and management’ (July 2-12, 2012)
National Defense University, P. R. China
Instructors: Xinjun Mao, Yongfang Liu, Dinghua Shi, Qiyue Cheng
Routine dynamics, Agent-based modeling, Computational social/organization science, Industrial systems engineering, etc.
Xiaotian Wang Member since: Fri, Mar 28, 2014 at 02:23 AM
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
Tatiana Filatova Member since: Tue, Oct 04, 2011 at 08:57 AM Full Member
I am Professor in Computational Resilience Economics at the University of Twente (the Netherlands), which I joined in 2010. In September 2017 I also joined University of Technology Sydney (Australia) as Professor of Computational Economic Modeling working with spatial simulation models to study socioeconomic impacts of disasters and emergence of resilience across scales. I was honored to be elected as a Member of the De Jonge Akademie of the Royal Dutch Academy of Sciences (DJA/ KNAW in 2016) and of Social Sciences Council (SWR/KNAW in 2017). From 2009 to 2015 I have been working part-time as an economist at Deltares – the leading Dutch knowledge institute in the field of water management – specializing in economics of climate change, with focus on floods and droughts management.
I am interested in the feedbacks between policies and aggregated outcomes of individual decisions in the context of spatial and environmental policy-making. The issue of social interactions and information diffusion through networks to affect economic behavior is highly relevant here. My research line focuses on exploring how behavioral changes at micro level may lead to critical transitions (tipping points/regime shifts) on macro level in complex adaptive human-environment systems in application to climate change economics. I use agent-based modelling (ABM) combined with social science methods of behavioral data collection on individual decisions and social networks. This research line has been distinguished by the NWO VENI and ERC Starting grants and the Early Career Excellence award of the International Environmental Modeling Society (iEMSs). In 2018 I was invited to serve as the Associate Editor of the Environmental Modelling & Software journal, where I have been a regular Member of the Editorial Board since 2013.
Steve Peck Member since: Fri, Apr 24, 2020 at 03:31 PM Full Member Reviewer
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.
Displaying 6 of 46 results for "Marco Alberti" clear search