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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Dr. Jiin Jung is a social psychologist and Assistant Professor in the Department of Psychology at Lehigh University. She also serves Secretary of the Computational Social Science of the Americas. Dr. Jung’s research focuses on how minority voices influence society and drive changes in social norms and cultural practices. She directs the Group Dynamics & Social Change Lab, which is dedicate to investigating psychological explanations for social change. Her lab explores topics such as minority influence on social change, minority responses to identity uncertainty and threat, and minority contributions to collective adaptation. Dr. Jung engages in policy initiatives geared toward democracy and gender equity.

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.

Annie Waldherr is Professor of Computational Communication Science at the Department of Communication at the University of Vienna. She studied Communication Science at the University of Hohenheim and the School of Journalism and Communication at the University of Oregon. She held positions at the Faculty of Social Sciences at the University of Hohenheim and the Institute for Media and Communication Studies at Freie Universität Berlin where she also obtained her PhD in 2011. Before joining the University of Vienna in September 2020, Annie Waldherr was Assistant Professor at the Department of Communication at the University of Münster.

I have been involved in agent-based modelling since the early nineties with a consistent attention to methdological improvement, institutional development and empirical issues. My mission is that ABM should be a routinely accepted research method (with a robust methodology) across the social sciences. To this end I have built diverse models and participated in research projects across economics, law, medicine, psychology, anthropology and sociology. I took a DPhil in economics on adaptive firm behaviour and then was involved in two research projects on money management and farmer decision making. Since 2006 I have worked at the Department of Sociology (now the School of Media, Communication and Sociology) at the University of Leicester. I was involved in the founding of JASSS and (more recently RofASSS https://rofasss.org) and have regularly served on the review panels for international conferences in the ABM community.

I received my BSc, MSc, and PhD from the University of Nottingham. My PhD focuses on the Agent-Based Modelling and Simulation (ABMS) of Public Goods Game (PGG) in Economics. In my thesis, a development framework was developed using software-engineering methods to provide a structured approach to the development process of agent-based social simulations. Also as a case study, the framework was used to design and implement a simulation of PGG in the continuous-time setting which is rarely considered in Economics.

In 2017, I joined international, inter-disciplinary project CASCADE (Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies) to further pursue my research interest in strategic modelling and simulation of human-centred complex systems. CASCADE, funded by the US National Institutes of Health (NIH), aims to develop agent-based models and systems-based models of the UK and US populations for the sequential and linked purposes of testing theories of alcohol use behaviors, predicting population alcohol use patterns, predicting population-level alcohol outcomes and evaluating the impacts of policy interventions on alcohol use patterns and harmful outcomes.