Displaying 10 of 402 results for "J Van Der Beek" clear search
Leonardo Grando is a Ph.D. at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
Dr. Aaron Bramson is principal investigator of the AI Strategy Center of GA technologies in Tokyo, Japan, as well as an Affiliate Researcher in the Department of General Economics of Ghent University in Belgium. His research specialty is complexity science, especially methodologies for modeling complex systems. Research topics span across disciplines: measures of polarization and diversity, belief measure interoperability, integrating geospatial and network analyses for measuring walkability and neighborhood identification, and myriad applications in artificial intelligence and data visualization. He received his Ph.D. from the University of Michigan in a joint program with the departments of Political Science and Philosophy as well as an M.S. in Mathematics from Northeastern University.
Complex systems, agent-based modeling, social simulation, computational models, network models, network theory, methodology, philosophy of science, ontology, epistemology, ethics, artificial intelligence, big data analysis, geospatial data analysis,
André Calero Valdez does research on Computational Communication Science investigating the influence of network structure and algorithms on communication flow using agent-based modeling.
Development and usage of demographic microsimulation tools and applications, in particular combining statistical modeling and social theory
Agent Based Modelling of energy consumer’s awareness diffusion. Role of smart metering in energy consumption. Social norm as limiting factor against rebound effects. Role of behavioral changes in energy efficiency.
Cheick Amed Diloma Gabriel Traore is a researcher specializing in modeling multi-agent systems. He earned his PhD from Cheikh Anta Diop University (UCAD) in Senegal. His doctoral research focused on the formalization and simulation of Sahelian transhumance as a complex adaptive system. Utilizing mathematical and computational techniques, he developed agent-based models to analyze the spatiotemporal dynamics of transhumant herds, taking into account factors such as herd behavior, environmental conditions, and socio-economic pressures.
To design the models for his dissertation, Cheick conducted extensive fieldwork in Senegal. He collaborated with interdisciplinary teams to collect data on transhumant practices within the Sahelian ecosystem. With this data, he created a multi-objective optimization framework to model the movement decisions of transhumants and their herds. Additionally, he developed a real-time monitoring system for transhumant herds based on discrete mathematics. His doctoral research was funded by the CaSSECS project (Carbon Sequestration and Sustainable Ecosystem Services in the Sahel).
Before pursuing his PhD,Cheick obtained both a master’s and a bachelor’s degree in mathematics from Nazi Boni University in Burkina Faso. During his studies, he developed a rectangular grid for image processing and applied the Hough transform to detect discrete lines. His master’s and bachelor’s degrees were funded by the Burkinabe government.
Currently,Cheick is an Assistant Professor at the Institute of Computer Engineering and Telecommunications at the Polytechnic School of Ouagadougou. In addition to his role in student training, he is working on integrating viability theory with agent-based modeling to address sustainable development challenges in rapidly changing and complex socio-economic systems. His research has been published in several renowned conferences and scientific journals, and he continues to actively contribute to the fields of complex systems modeling and image processing.
Agent Based Modeling, Machine Learnig, Deep Learning, Numerical Analysis
To tackle the scientific challenges proposed by landscape dynamics and cooperation processes, I have developed a research methodology based on field work and companion modelling (ComMod) combined with the formalisation of the observed processes and agents based models.
This approach offers the possibility to understand : spatial, social, cultural and / or economic conditions that take place on territories, and to provide prospective scenarios.
These methods have been applied in various contexts: steep slope vineyards landscapes (2011), water resource management cooperation (2015), vegetation cover in dry climate (2017). The established research networks are still active through sustained collaborations and activities.
My technical expertise grew and evolved through investment in several workgroups: MAPS Team (Modelling Applied to Space Phenomena), OSGeo (president of the OSGeo’s French chapter between 2013 and 2016, member of the OSGeo-international chapter since 2015), various initiatives around modelling, exploration and sensibility analysis of spatial patterns behaviours, and more generally in Free Software communities.
I am interested in the socio-environmental conditions for the emergence of cooperation and mutual aid in social systems and mainly with regard to renewable resources. I consider in this context that Commons are a spatial manifestation of mutual aid.
From a technical point of view, I am very interested in the questions of model exploration (HPC), which led me to integrate the OpenMole community and to contribute to discussions about heuristic exploration.
MY research aims to give artists better 3D references and scene reconstructions which can be directly fed into the creative pipeline. This is motivated by increasing public demand for detailed, complex 3D worlds and the resulting demand this places on world design artists.
This project lookings at developing acquisition and modelling technologies that provide more than just a visual reference: in the context of this project, visual acquisition and reconstruction methods shall be developed that provide richer, three-dimensional references, and that ultimately yield scene reconstructions that can directly be fed into the content creation pipeline. The project will focus on natural environments (as opposed to urban scenes) and may combine multi-spectral imaging, wide-baseline stereo reconstruction and semantic scene analysis to obtain approximate procedural representations of natural scenes.
Ecological modeller; behaviour of pollinating insects (especially bumblebees) in GIS landscapes. Hope to apply ABM methods to model some of the field data we have collected
Displaying 10 of 402 results for "J Van Der Beek" clear search