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Lu Ping is a dedicated researcher in interdisciplinary fields including artificial intelligence (AI), digital economy, technological innovation, and industrial economics. Currently serving as an Associate Research Fellow at the China Academy of Information and Communications Technology (CAICT), Lu Ping focuses on examining the impacts of digital technologies (e.g., AI, big data, and IoT) on economic growth, industrial ecosystems, policy formulation, and societal ethics through multidimensional data modeling and empirical research.
Representative Academic Contributions:
1. AI Development and Societal Implications
A Brief History of Artificial Intelligence Development in China (2017): Explored the technological evolution and policy-driven pathways of China’s AI industry.
Ethical Dilemmas Faced by AI Algorithms (2018): Analyzed ethical challenges such as algorithmic bias and data privacy, proposing governance frameworks.
A Brief History of the Evolution of Smart Hardware in China (2018): Systematically reviewed the technological iterations and market dynamics of China’s smart hardware sector.
2.Technological Innovation and Industrial Economics
An Empirical Analysis of Technological Innovation Driving Growth in Internet Companies: Evidence from A-Share Listed Internet Firms in Shanghai and Shenzhen (2019).
Research on Competitiveness Measurement of Frontier Emerging Industries Based on Data Envelopment Analysis (DEA) Models (2019).
3.Digital Economy and Market Behavior
Correlation Analysis of Crowdfunding Behavior and Funding Performance for Internet Products: A Bayesian Approach Based on JD.com Crowdfunding Data (2018): Uncovered nonlinear relationships between user participation and project success rates using crowdfunding platform data.
Analyzing the Effects of Developer and User Behavior on Mobile App Downloads (2019): Built predictive models for app market performance based on user behavior data.
4.Policy Simulation
General Equilibrium Analysis of Beijing’s Water Supply and Consumption Policies: A Computable General Equilibrium (CGE) Model-Based Approach (2015).
Impact Analysis of EU Food Safety Standards on China’s Food Industry: A Dynamic Global Trade Analysis Project (GTAP) Model-Based Study (2015).
Academic Contributions:
Pioneered interdisciplinary paradigms in industrial economics research by integrating perspectives from econometrics, data science, and sociology. Published high-impact research in AI ethics, digital economy policies, and resource-environmental economics, providing decision-making references for academia and policymakers.
My research focuses on the interdisciplinary nexus of artificial intelligence (AI), digital economy, technological innovation, and industrial economics, with an emphasis on understanding how digital technologies reshape economic structures, policy frameworks, and societal norms. Key areas of interest include:
Amineh Ghorbani is an assistant professor at the Engineering Systems and Services Department, Delft University of Technology, the Netherlands. She is also an affiliated member of the “Institutions for Collective Action” at Utrecht University. She obtained her M.Sc. in Computer Science (Artificial intelligence) from University of Tehran (Iran) (2009, honours) and her PhD from Delft University of Technology (2013, cum laude).
During her PhD, Amineh developed a meta-model for agent-based modelling, called MAIA, which describes various concepts and relations in a socio-technical system. This modelling perspective helped her develop a modelling paradigm that she refers to as institutional modelling.
Her current area of research is understanding the emergence and dynamics of institutions (set of rule organizing human society) using modelling. She is interested in how bottom-up collective action emerges and how institutions emergence and change within communities.
collective action
institutional emergence
evolution of institutions
community energy systems
Anna Sikora is an Associate Professor in the Computer Architecture and Operating System Department at Autonomous University of Barcelona (UAB).
She got the BS degree in computer science in 1999 from Technical University of Wroclaw (Poland). She got the MSc in computer science in 2001 and in 2004 the PhD in computer science, both from Autonomous University of Barcelona (Spain).
Since 1999 her investigation is related to parallel and distributed computing. Her current main interests are focused on high performance parallel applications, performance models, automatic performance analysis and dynamic tuning. She has been involved in programming tools for automatic and dynamic performance tuning on cluster and Grid environments, as well as in exa-scale systems.
High performance parallel computing, parallel applications, performance models, automatic performance analysis, dynamic tuning. Performance tools for automatic and dynamic performance tuning on HPC systems. Agent-based modelling systems.
Isaac IT Ullah, PhD, (Arizona State University 2013) Dr. Ullah is a computational archaeologist who employs GIS and simulation modeling to understand the long-term dynamics of humans and the Earth System. Dr. Ullah is particularly interested in the social and environmental changes surrounding the advent of farming and animal husbandry. His focus is on Mediterranean and other semi-arid landscapes, and he conducts fieldwork in Jordan, Italy, and Kazakhstan. His field work includes survey for and excavation of early agricultural sites as well as geoarchaeological analyses of anthropogenic landscapes. His specialties include landscape evolution, complex adaptive systems science, computational methods, geospatial analysis, and imagery analysis.
Computational Archaeology, Food Production, Forager-Farmer transition, Neolithic, Agro-pastoralism, Erosion Modeling, Anthropogenic Landscapes, Geoarchaeology, Modeling and Simulation, GIS, Imagery Analysis, ABM, Mediterranean
My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.
I am currently a Senior Lecturer in Computational Epidemiology at Western Sydney University, School of Computer, Data and Mathematical Science where I am also a member of Translational Health Research Institute (THRI). I am a research associate at the Brain and Mind Centre, Sydney University and Adjunct Senior Lecturer at Psychiatry Monash Health, Monash University.
My work is in the areas of dynamic data-driven computer simulation and systems science. The product of my work is decision and research support software that applies agent and discrete event based models, and metaprogramming techniques to solve complex problems.
I am currently Chief Investigator (CI) on an international grant funded by Botnar foundation as well as on a MRFF funded grant with Brain and Mind Centre, The University of Sydney and an Associate Investigator (AI) on Suicide Prevention Australia funded research at The University of Melbourne. In he last 5 years I have been CI on 7 grants and commissioned research projects and AI on 1 grant with total value of over $8 million AUD.
Agent based modelling and simulation.
Mental heath and wellbeing.
S.R. Aurora, also known as Mai P. Trinh, is an Assistant Professor of Management at The University of Texas Rio Grande Valley. Her interdisciplinary work intersects leadership, complex systems science, education, technology, and inclusion. Her research harnesses technology to cultivate future leaders and helps people thrive in our volatile, uncertain, complex, and ambiguous (VUCA) high-tech world, aligning with four United Nations’ sustainable development goals: Quality education (#4), Gender equality (#5), Decent work and economic growth (#8), and Reduced inequalities (#10). She has published in top-tiered peer-reviewed journals such as The Leadership Quarterly and The Academy of Management Learning and Education and received multiple national and international awards for her research, teaching, and mentoring. Dr. Aurora earned her doctoral degree in Organizational Behavior from the Weatherhead School of Management at Case Western Reserve University in 2016.
Leader development, leading complex systems, agent-based modeling, experiential learning, innovations in online education
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.
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).
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