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About me
Name: Dr. Julia Kasmire
Position: Post-doctoral Research Fellow
Where: UK Data Services and Cathie Marsh Institute at the University of Manchester.
Short Bio
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).
Additional Resources
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
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.
Computational Social Science, Social Simulation, Innovative Methods, Agent-based Modelling, Serious game
Future Studies, AI Sociology, Societal Change, and some classical sociological topics (e.g. Social Mobility and Unequality, Education, Collective Action)
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Angelos Chliaoutakis received his PhD in Electronic & Computer Engineering in 2020 at Technical University of Crete (TUC), Greece. During 2005-2020 he was a research assistant at the Intelligent Systems Laboratory of TUC, participating in several research projects associated with NLP, semantic similarity and ontology based information systems. Since 2010 he is also a research assistant at the Laboratory of Geophysical - Satellite Remote Sensing and Archaeo-environment (GeoSat ReSeArch Lab) of the Institute for Mediterranean Studies of Foundation for Research and Technology (IMS-FORTH), were he is involved in various research projects related to the full-stack development of Geographical Information Systems (GIS), web-based GIS applications and Geoinformatics in the cultural and archaeological domain. This ultimately transformed his interest and research direction towards computational archaeology, in particular, agent-based modeling and simulation, while intertwining ideas and approaches from Artificial Intelligence, Multi-agent Systems and GIS.
Research activities range between Computer Science, Information Systems and Natural Language Processing (NLP), Agent-based modeling/simulation (ABM), Artificial Intelligence (AI) and Multi-Agent Systems (MAS) and Geographical Information Science (GIScience).
Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)
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 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.
I study he role of biologically-based motivations in the formation of socio-political phenomena using agent-based modelling techniques. In particular I look at how behaviour inhibition and activation, as well as interpersonal attitudes can shape the emergence of complex polities.
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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.
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