Displaying 10 of 503 results for "Bin-Tzong Chi" clear search
The Global Resource Observatory (GRO)
The Global Resource Observatory is largest single research project being undertaken at the GSI, it investigates how the scarcity of finite resources will impact global social and political fragility in the short term. The ambitious three year project, funded by the Dawe Charitable Trust, will enable short term decision making to account for ecological and financial constraints of a finite planet.
GRO will include an open source multidimensional model able to quantify the likely short term interactions of the human economy with the carrying capacity of the planet and key scarce resources. The model will enable exploration of the complex interconnections between the resource availability and human development, and provides projections over the next 5 years.
Data and scenarios will be geographically mapped to show the current and future balance and distribution of resources across and within countries. The GRO tool will, for the first time, enable the widespread integration of the implications of depleting key resource into all levels of policy and business decision-making.
This is Saeed Abdolhosseini. I am very interested in the area of agent based modeling and it is about 3 years that I am working on Agent-Based Modeling. I have a good experience of working with Netlogo &Repast simphony & Anylogic. I have developed a few ABM application.
Specialties: Agent-based models of social systems
Agent Based Modeling
SHIPENG SUN is an Assistant Professor in the Department of Geography and Environmental Science at Hunter College and the Earth and Environmental Sciences Program at Graduate Center, The City University of New York, New York, NY 10065. E-mail: [email protected].
Sociospatial network analysis, geovisualization, GIS algorithms, agent-based complexity modeling, human–environment systems, and urban geography
Eletronic Engineer with specialization in Computer Science and a passion for Artificial Intelligence, Simulation, Programming, and many other tech topcis . One life is really not enough to learn and experiment all cool things that are out there. Love also learning languages: Portuguese, English, French, Italian, and German.
I am a researcher in data science for sustainability, working at the intersection of society, politics, economy, and the environment. My work integrates statistics, artificial intelligence, and complex systems approaches to generate robust, data-driven evidence that supports decision-making in complex socio-environmental contexts.
My research focuses on understanding and modeling socio-ecological systems, with the goal of improving sustainability outcomes through interdisciplinary analysis and innovative analytical tools.
My research interests are organized around four main areas:
🌱 Socio-ecological systems dynamics
I study the interactions between human societies and ecosystems, with particular attention to the social, economic, and political processes that shape these dynamics.
💚 Nature’s values
I explore the diverse ways in which people value nature and work on integrating these perspectives into decision-making processes and public policy design.
🦋 Biodiversity management and conservation
I apply computer vision, statistical modeling, and spatial analysis to species classification and monitoring, generating evidence to support biodiversity management and conservation strategies.
🏛️ Governance and public policy
I analyze policy integration and coherence using quantitative and data-driven methods, aiming to improve policy design, implementation, and decision-making processes.
Overall, my research seeks to integrate interdisciplinary approaches to strengthen sustainability, generating knowledge and innovative tools based on data science and artificial intelligence that support both public policy development and the management and conservation of socio-ecological systems.
The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
Sr Machine Learning Engineer, Google Developer Expert in Cloud and Machine Learning. CompTIA Security+, AWS certified Machine Learning specialty.
Generative AI, LLMs, Multi-Agent Modeling, Agent-Based Modeling, Cellular Automata, Graph Networks, Deep Learning, Social Sciences
The main research area is operation research in logistics with a focus on logistic cluster development and innovative technology usage. Due to mathematical background, Gružauskas focuses on quantitative analysis by conducting simulations, stochastic and dynamic models and other analytical approaches to amplify the developed theories. Gružauskas also is working as a freelance data analyst with a focus on statistical analysis, web scraping and machine learning.
The Ph.D. research project is mainly focused on the study of the influence of emotional intelligence inside decision-making processes and on the social and emotional aspects of organizations.Furthermore, the research has taken into account the generative science paradigm: in this way, the general aim is the development of social simulations able to account organizational processes related with emotions and with the emotional intelligence from the bottom-up.
Displaying 10 of 503 results for "Bin-Tzong Chi" clear search