Andrew Crooks is an Associate Professor with a joint appointment between the Computational Social Science Program within the Department of Computational and Data Sciences and the Department of Geography and GeoInformation Science, which are part of the College of Science at George Mason University. His areas of expertise specifically relate to integrating agent-based modeling (ABM) and geographic information systems (GIS) to explore human behavior. Moreover, his research focuses on exploring and understanding the natural and socio-economic environments specifically urban areas using GIS, spatial analysis, social network analysis (SNA), Web 2.0 technologies and ABM methodologies.

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.

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.

Dr. Mariam Kiran is a Research Scientist at LBNL, with roles at ESnet and Computational Research Division. Her current research focuses on deep reinforcement learning techniques and multi-agent applications to optimize control of system architectures such as HPC grids, high-speed networks and Cloud infrastructures.. Her work involves optimization of QoS, performance using parallelization algorithms and software engineering principles to solve complex data intensive problems such as large-scale complex decision-making. Over the years, she has been working with biologists, economists, social scientists, building tools and performing optimization of architectures for multiple problems in their domain.

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Olá, I’m Daniel! 👋

I’m an R(esearcher) at the University of São Paulo (USP) working on complex systems and data science. My family name is actually KACHvartanian, but I go by Vartanian to save everyone from a linguistic workout.

I love building open-source tools, being part of active communities, and working with the R, Python, and NetLogo programming languages. When I’m not coding, I’m likely watching a good movie, seeing friends, wandering through new places, or tinkering with some obscure new thing that may or may not go anywhere.

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.

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.