Displaying 10 of 178 results for "Benjamin I Czaczkes" clear search
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.
Complex Systems
Agent-based Models
System Dynamics
Innovation
Economics
Organizational Development
Aniruddha Belsare is a disease ecologist with a background in veterinary medicine, interspecific transmission, pathogen modeling and conservation research. Aniruddha received his Ph.D. in Wildlife Science (Focus: Disease Ecology) from the University of Missouri in 2013 and subsequently completed a postdoctoral fellowship there (University of Missouri, May 2014 – June 2017). He then was a postdoctoral fellow in the Center for Modeling Complex Interactions at the University of Idaho (June 2017 - March 2019) and later a Research Associate with the Boone and Crockett Quantitative Wildlife Center, Michigan State University (March 2019 - Jan 2021). He was a Research Scientist in the Civitello Disease Ecology Lab at Emory University from Jan 2021 to Jan 2023. Currently, Aniruddha is an Assistant Professor of Disease Ecology at the College of Forestry, Wildlife & Environment / College of Veterinary Medicine at Auburn University.
My research interests primarily lie at the interface of ecology and epidemiology, and include host-pathogen systems that are of public health or conservation concern. I use ecologic, epidemiologic and model-based investigations to understand how pathogens spread through, persist in, and impact host populations. Animal disease systems that I am currently working on include canine rabies, leptospirosis, chronic wasting disease, bighorn sheep pneumonia, raccoon roundworm (Baylisascaris procyonis), chytridiomycosis, and Lyme disease.
Antônio Sousa is a biologist with a background in medical entomology, disease ecology, statistical and computational modeling. Antônio has a Ph.D. (2018) and Master (2014) in Science from the School of Public Health at the University of São Paulo, Brazil. Currently, he is a postdoctoral fellow in the same institution.
My research interest lies in the study of the transmission and dispersal dynamics of vector-borne diseases. I have been working on the development of statistical, mathematical and computational models to understand bioecology of mosquitoes and to predict the transmission dynamics of pathogens transmitted by these insects.
I’ve been building cyberinfrastructure and research software for computational social science and the study of complex adaptive systems at Arizona State University since 2006. Past and current projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, Synthesizing Knowledge of Past Environments (SKOPE), the Port of Mars, and CoMSES Net, where I serve as co-director and technical lead.
I also work to improve the state of open, transparent, reusable, and reproducible computational science as a Carpentries instructor and maintainer for the Plotting and Programming in Python and Good Enough Practices for Scientific Computing lessons, currently co-chair the Consortium of Scientific Software Registries and Repositories and Open Modeling Foundation Cyberinfrastructure Working Group, and serve on the DataCite Services and Technology Steering Group and CSDMS’s Basic Model Interface open source governance council.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable, reproducible, and interoperable scientific computation.
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
I am interested in questions of method, and in the application of computational social models to a wide variety of national security questions (such as counterterrorism and counterinsurgency) as well as decision-making around complex natural resources such as water. My methods interest center on the use of qualitative social theory to inform the structure of computational social models, and the ways in which such models handle qualitative data. This raises questions around the nature of data and the ways in which computational social models convey information to decision-makers.
Senior (Tenure-Track) Assistant Professor in Work and Organizational Psychology (WOP) at the Human Sciences Department of Verona University. My expertise lies in organizational behavior, individual differences and decision-making at work, and social dynamics in the applied psychology field. In the field of fundamental research my studies explore the role of individual antecedents (e.g., Personality traits, Risk attitudes, etc.) in relation to classic I/O models (e.g., Job Demands-Resources model, Effort-Reward model, etc.). My applied research focuses on the development of interventions and policies for enhancing decision-making, and in turn well-being and job performance. Finally, in industrial research, my research aims to better integrate cognitive and behavioral theories (e.g., Theory of Planned Behavior, Prospect theory, etc.) for designing predictive models – based on agents – of social and organizational behaviors.
Doctor and Magister in Informatics by the Girona University (Spain), Telematics Engineer and Systems Technologist by the Francisco José de Caldas University (Bogotá, Colombia), Specialist in Databases Management, and Specialist in Higher Education. Currently, associate professor and researcher at the Fundación Universitaria Konrad Lorenz (Bogotá, Colombia). Academic leader of the Konrad IA project (IA - Artificial Intelligence). Associated researcher by the science and technology Colombian ministry.
CoMSES.Net is a good community space to share knowledge regarding agent based and computational models that are built based upon a wide variety of contexts (social, political, educational, scientific, biological, etc.). Thus, the CoMSES.Net should be known in all regions around the world. Moreover, as I belong to the Spanish-speaking community, it would be very interesting to publicize what the network does in Spanish-speaking countries.
Research topics: Inmersive Technologies, Educational Technologies, Web Accessibility and Usability, Sematic Web, Artificial Intelligence.
I am strongly interested in ecological modeling and complex system and truly enjoyed working with a variety of tools to uncover patterns in empirical data and explore their ecological and evolutionary consequences. My primary research is to conduct research in the field of ‘ecological complexity’, including the development of appropriate descriptive measure to quantify the structural, spatial and temporal complexity of ecosystem and the identification of the mechanism that generate this complexity, through modeling and field studies.
Currently investigated is how biological characteristics of invasive species (dispersal strategies and demographic processes) interact with abiotic variables and resource distribution to determine establishment success and spread in a complex heterogeneous environment (Individual based modelling integrated with GIS technologies).
Ifigeneia Koutiva (female) is a senior environmental engineer, holding a PhD in Civil Engineering (NTUA), a Postgrad Diploma in Water Resources and Environmental Management (Un. of Belgrade - e-learning), an MSc in Environmental Technology (Imperial College London) and an MSc in Mining and Metallurgy Engineering (NTUA). Her PhD was funded by the Greek Ministry of Education through Heracleitous II scholarship. She is currently a postdoctoral scholar of the State Scholarship Foundation (IKY) for 2020 - 2021. She has 10 years of experience in various EU funded research projects, both as a researcher and as a project manager, in the fields of socio-technical simulation, urban water modelling, modelling and assessment of alternative water technologies, artificial intelligence, social quantitative research, KPI and water indicators development and assessment and analysis of large data sets. She is very competent with programming for creating ICT tools for agent based modelling and data analysis tools and she is an experienced user of spatial analysis software and tools. She is also actively involved in the design and implementation of numerous consultation workshops and conferences. She has authored more than 20 scientific journal articles, conferences articles and research reports.
My research interests lay within the interface of social, water and modelling sciences. I have created tools that explore the effects of water demand management policies in domestic urban water demand behaviour and the effects of civil decision making in flood risk management. I am interested in agent based modelling, artificial intelligence techniques, the creation of ABM tools for civil society, Circular Economy, distributed water technologies and overall urban water management.
Displaying 10 of 178 results for "Benjamin I Czaczkes" clear search