Displaying 10 of 422 results for "J Van Der Beek" clear search
My initial training was in cadastre and geodesy (B.Eng from the Distrital University, UD, Colombia). After earning my Master’s degree in Geography (UPTC, Colombia) in 2003, I worked for the “José Benito Vives de Andreis” marine and coastal research institute (INVEMAR) and for the International Center for Tropical Agriculture (CIAT). Three years later, in 2006, I left Colombia to come to Canada, where I began a PhD in Geography with a specialization in modelling complex systems at Simon Fraser University (SFU), under the direction of Dr. Suzana Dragicevic (SAMLab). In my dissertation I examined the topic of spatial and temporal modelling of insect epidemics and their complex behaviours. After obtaining my PhD in 2011, I began postdoctoral studies at the University of British Columbia (2011) and the University of Victoria (2011-2013), where I worked on issues concerning the spatial and temporal relationships between changes in indirect indicators of biodiversity and climate change.
I am a Full Professor in the Department of Geography at the University of Montreal. My research interests center around the incorporation of artificial intelligence and machine learning techniques into the development Agent-Based Models to solve complex socio-ecological problems in different kind of systems, such as urban, forest and wetland ecosystems.
The core of my research projects aim to learn more about spatial and temporal interactions and relationships driving changes in our world, by focusing on the multidisciplinary nature of geographical information science (GIScience) to investigate the relationships between ecological processes and resulting spatial patterns. I integrate spatial analysis and modeling approaches from geographic information science (GIScience) together with computational intelligence methods and complex systems approaches to provide insights into complex problems such as climate change, landscape ecology and forestry by explicitly representing phenomena in their geographic context.
Specialties: Agent-based modeling, GIScience, Complex socio-environmental systems, Forestry, Ecology
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:
Current main research interests are concerned on diffusion of ICT among social actors of territorial systems: citizens(individuals and households), enterprises and governmental bodies. Most used methodological tools are , so far, multivariate statistics and Social Network Analysis.
I’d like to apply an ABM approach in the context of my PhD research project, aimed to observe the different modes of collaboration among universities and enterprises and tehir different effectiveness in terms of creation and spread of new knowledge.
My interests are focused on the development of new methodologies capable of exploring the complex relations between time, space and human behavior. Simulation, game theory and spatial analysis are some of the techniques that I use to explore different research questions, from the relation between environment and culture to the evolution of warfare.
I’m also the project manager of Pandora, an open-source ABM platform specifically designed for executing large scale simulations in High-Performance Computing environments.
I study human dimensions of natural resource management and resource use by under-represented populations—often in developing nations—to enhance our understanding of conflicts involving land use, natural resources, and conservation from an interdisciplinary, systematic lens. My research spans subjects such as common pool resource management and policy, decentralization, and land use/land cover change drivers and trends relating to population rise and environmental change.
Arpan Jani received his PhD in Business Administration from the University of Minnesota in 2005. He is currently an Associate Professor in the Department of Computer Science and Information Systems at the University of Wisconsin – River Falls. His current research interests include agent-based modeling, information systems and decision support, behavioral ethics, and judgment & decision making under conditions of risk and uncertainty.
agent-based modeling; behavioral ethics; information systems and decision support; project management; judgment & decision making under conditions of risk and uncertainty.
I received a Ph.D. in Economics at the University of Namur (Belgium) in June 2012 with a thesis titled “Essays in Information Aggregation and Political Economics”.
After two years at the Research Center for Educational and Network Studies (Recens) of the Hungarian Academy of Sciences, I joined the Department of Economics “Marco Biagi” of the University of Modena and Reggio Emilia in January 2015 and then the Department of Agricultural and Food Sciences of the University of Bologna.
I am currently a Lecturer in Financial Computing at the Department Computer Science (Financial Computing and Analytics group) - University College London. Moreover I am an affiliated researcher of the DYNAMETS - Dynamic Systems Analysis for Economic Theory and Society research group and an affiliate member of the Namur Center for Complex Systems (Naxys).
My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.
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.
Displaying 10 of 422 results for "J Van Der Beek" clear search