Displaying 10 of 226 results for "Rolf Anker Ims" clear search
Dr. Andreu Moreno Vendrell got the BS degree in Telecommunications Engineering in 1995 and the PhD in Telecommunications Engineering in 2000, both from Universitat Politècnica de Catalunya (Spain). Since 2005 his research is related to parallel and distributed computing. His main interests are focused on high performance parallel applications, automatic performance analysis and dynamic tuning, and agent based simulation systems. He has been involved in the definition of performance models for automatic and dynamic performance tuning and in the development of a new benchmark for agent based frameworks. He is lecturer at the Escola Universitària Salesiana de Sarrià, associated college of Universitat Autònoma de Barcelona. He is IEEE member.
Agent-based systems
Amin is a PhD student in the quantitative and systems biology graduate program at UC Merced. He has been passionate about entrepreneurship since his undergraduate years in his hometown of Isfahan and then later in Bologna, Italy, where he completed his masters. Once a recipient of the Innovators Under 35 Award in Italy, he believes there is massive opportunity for society to train and motivate younger minds to acquire an entrepreneurial mindset, along with entrepreneurship skills.
Entrepreneurship, management, mathematical modeling, agent based modeling.
Garry Sotnik is a lecturer at the Stanford Doerr School of Sustainability, teaching human adaptation to climate change, decision-making, and transformative social change.
complexity, agent-based modeling, cognition
My research aims to explore the potential of network science for the archaeological discipline. In my review work I confront the use of network-based methods in the archaeological discipline with their use in other disciplines, especially sociology and physics. In my archaeological work I aim to develop and apply network science techniques that show particular potential for archaeology. This is done through a number of archaeological case-studies: archaeological citation networks, visibility networks in Iron Age and Roman southern Spain, and tableware distribution in the Roman Eastern Mediterranean.
I am currently completing a PhD on information sharing for natural resources management. Research is based on case studies on oyster farming, in the Thau Basin, France and in New South Wales, Australia
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In Fall 2023, he is a Visiting Research Scholar at SUNY Binghamton in NY.
agent-based simulations
social network analysis
complex systems
big data analysis
statistical learning
computational social science
IRPact - An integrated agent based modeling approach in innovation diffusion
Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.
My main research field is health economic modeling with the main focus on sexually transmitted diseases. We are trying to build a agent-based model using the FLAME-framework (www.flame.ac.uk).
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