Fabian Adelt graduated in computer-sciences with a minor in sociology of technology (degree: Diplom-Informatiker) at TU Dortmund University in 2011. Currently, he is research fellow at the Technology Studies Group and involved in the project “Collaborative Data- and Risk-Management in Future Grids – A Simulation Study” (KoRiSim). Between 2012 and 2015 he worked on the project “Mixed Modes of Governance as a Means of Risk Management in Complex Systems” (RiskSim). His research interests entail agent-based modelling and simulating of socio-technical systems, especially focussing on governance issues and actors’ reactions on interventions. Experience covers the fields of mobility and energy.

My research uses modeling to understand complex coupled human and natural systems, and can be generally described as computational social science. I am especially interested in modeling water management systems, in both archaeological and contemporary contexts. I have previously developed a framework for modeling general archaeological complex systems, and applied this to the specific case of the Hohokam in southern Arizona. I am currently engaged in research in data mining to understand contemporary water management strategies in the U.S. southwest and in several locations in Alaska. I am also a developer for the Repast HPC toolkit, an agent-based modeling toolkit specifically for high-performance computing platforms, and maintain an interest in the philosophy of science underlying our use of models as a means to approach complex systems. I am currently serving as Communications Officer for the Computational Social Science Society of the Americas.

I have a BS in Earth Sciences and a PhD in Resource and Environmental Economics. I have more than 25 years of experience doing research and teaching and advising students in systems thinking, scenario development, simulation, and ecological economics. Presently, I am an Associate Professor in the Department of Computational & Data Sciences at George Mason University, and a member of the Center for Social Complexity. I teach the introductory courses on Computational Social Sciences at both the undergraduate and graduate levels, as well as beginning and advanced courses in complex systems, modeling, and simulation. My current research focuses on the use of scenario development and integrated modeling as applied to social-ecological systems. My recent work has focused on applying these to issues related to climate change economics and policy, including new technologies for greenhouse gas removal and solar radiation management.

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.

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.

Dr. 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, Dr. Traore 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, Dr. Traore 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, Dr. Traore 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.