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Dr. William G. Kennedy, “Bill,” is continuing to learn in a third career, this time as an academic, a computational social scientist.
His first a career was in military service as a Naval Officer, starting with the Naval Academy, Naval PostGraduate School (as the first computer science student from the Naval Academy), and serving during the Cold War as part of the successful submarine-based nuclear deterrent. After six years of active duty service, he served over two decades in the Naval Reserves commanding three submarine and submarine-related reserve units and retiring after 30 years as a Navy Captain with several personal honors and awards.
His second career was in civilian public service: 10 years at the Nuclear Regulatory Commission and 15 years with the Department of Energy. At the NRC he rose to be an advisor to the Executive Director for Operations and the authority on issues concerning the reliance on human operators for reactor safety, participating in two fly-away accident response teams. He left the NRC for a promotion and to lead, as technical director, the entrepreneurial effort to explore the use of light-water and accelerator technologies for the production of nuclear weapons materials. That work led to him becoming the senior policy officer responsible for strategic planning and Departmental performance commitments, leading development of the first several DOE strategic plans and formal performance agreements between the Secretary of Energy and the President.
Upon completion of doctoral research in Artificial Intelligence outside of his DOE work, he began his third career as a scientist. That started with a fully funded, three-year post-doctoral research position in cognitive robotics at the Naval Research Laboratory sponsored by the National Academy of Science and expanding his AI background with research in experimental Cognitive Science. Upon completion, he joined the Center for Social Complexity, part of the Krasnow Institute for Advanced Study at George Mason University in 2008 where he is now the Senior Scientific Advisor. His research interests range from cognition at the individual level to models of millions of agents representing individual people. He is currently leading a multi-year project to characterize the reaction of the population of a mega-city to a nuclear WMD (weapon of mass destruction) event.
Dr. Kennedy holds a B.S. in mathematics from the U.S. Naval Academy, and Master of Science in Computer Science from the Naval PostGraduate School, and a Ph.D. in Information Technology from George Mason University and has a current security clearance. Dr. Kennedy is a member of Sigma Xi, the American Association for the Advancement of Science (AAAS), the Association for Computing Machinery (ACM), and a life member of Institute of Electrical and Electronics Engineers. He is a STEM volunteer with the Senior Scientists and Engineers/AAAS Volunteer Program for K-12 science, technology, engineering, and mathematics education in the DC-area schools.
Cognitive Science, Computational Social Science, Social Cognition, Autonomy, Cognitive Robotics
Prof. Christian E. Vincenot is by nature an interdisciplinary researcher with broad scientific interests. He majored in Computer Science / Embedded Systems (i.e. IoT) at the Université Louis Pasteur (Strasbourg, France) while working professionally in the field of Computer Networking and Security. He then switched the focus of his work towards Computational Modelling, writing his doctoral dissertation on Hybrid Modelling in Ecology, and was awarded a PhD in Social Informatics by Kyoto University in 2011 under a scholarship by the Japanese Ministry of Research. He subsequently started a parallel line of research in Conservation Biology (esp. human-bat conflicts) under a postdoctoral fellowship of the Japanese Society for the Promotion of Science (JSPS) (2012-2014). This led him to create the Island Bat Research Group (www.batresearch.net), which he is still coordinating to this date. In 2014, he was appointed as the tenured Assistant Professor of the Biosphere Informatics Laboratory at Kyoto University. He also been occupying editorial roles for the journals PLOS ONE, Frontiers in Environmental Science, and Biology. In 2020, he created Ariana Technologies (www.ariana-tech.com), a start-up operating in the field of Data Science/Simulation and IoT for crisis management.
Prof. Vincenot’s main research interests lie in the theoretical development of Hybrid Mechanistic Simulation approaches based on Individual/Agent-Based Modeling and System Dynamics, and in their applications to a broad range of systems, with particular focus on Ecology.
I am a University Academic Fellow (UAF) in the School of Geography at the University of Leeds. My research areas are agent-based modelling, decision making in complex systems, AI and multi-agent systems, urban analytics and housing markets. I obtained PhD in Economics from Iowa State University under supervisor Prof. Leigh Tesfatsion in 2014. I worked as a researcher at the James Hutton Institute in Aberdeen, Scotland between 2014 and 2019. I joined the University of Leeds as a UAF of Urban Analytics in 2019. I am originally from Shanghai, China.
My main research areas are agent-based modelling, urban analytics and complex decision making enabled by AI. I am interested in the bottom-up transition of complex urban systems under major socio-economic and environmental shocks, such as climate change and the fourth industrial revolution. I want to understand how cities as self-organised complex systems respond to external shocks and evolve under a constantly changing environment. In the past, I have looked at various aspects of urban systems, including the housing market, the labour market, transport and energy system. I am also interested in decision making in complex systems. For example, I have studied the decision to become a vegetarian/vegan under social influence. I have also looked at global food trade in a complex trade network and the resulting food and nutrition security. Recently, I am interested in applying AI algorithms especially reinforcement learning in multi-agent systems, including applications of AI in urban adaptation to climate change, housing market dynamics and criminal behaviour in an urban system.
He is a member of IEEE, a computer scientist, an Information Technologist, and a Research Lab Head at the Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda. My research broadly integrates and focuses on developing principled computationally and statistically efficient models and algorithms for various machine learning problems in Smart Agriculture, Ecological Informatics, Computer Vision, Applied AI, Cybersecurity and Privacy, and Smart Cities. I attained a Bachelor in Information Technology at the Faculty of Science & Computing, Ndejje University, Kampala, Uganda; a Master in Information Technology Engineering (Computer and Communication Networks); and PhD in Computer Science Universiti Brunei Darussalam, Brunei. He has received additional training from, among others, the National Institutes of Health, US Department of Health and Human Services, and the Bloomberg School of Public Health, USA. Hundreds of scholarly publications, including those in prestigious peer-reviewed journal articles, numerous IEEE International, non-IEEE Conference proceedings, book chapters, and books have been published. Reviewer/editorial support of over twelve (Scopus, Compendex (Elsevier Engineering Index), and WoS International Journals, including Expert Systems With Applications, Scientific Reports and Computers and Electronics in Agriculture. I served in several capacities, including being departmental support for Mathematics for Data Science, Advanced Topics in Computing, and Advanced Algorithms. Prior to this, I served as a community data officer at Pace-Uganda, a research associate at TechnoServe, a research assistant at PSI-Uganda, a research lead at the Socio-economic Data Centre (SEDC-Uganda) and ag. managing director at Asmaah Charity Organisation.
Computer Vision, Artificial Intelligence, Security and Privacy, Smart Agriculture / Digital Agriculture, Health Computing, Digital Image Processing,
Social Networks Analysis, Sustainable Computing, Ecological Informatics, Smart Computing
I am Professor in Computational Resilience Economics at the University of Twente (the Netherlands), which I joined in 2010. In September 2017 I also joined University of Technology Sydney (Australia) as Professor of Computational Economic Modeling working with spatial simulation models to study socioeconomic impacts of disasters and emergence of resilience across scales. I was honored to be elected as a Member of the De Jonge Akademie of the Royal Dutch Academy of Sciences (DJA/ KNAW in 2016) and of Social Sciences Council (SWR/KNAW in 2017). From 2009 to 2015 I have been working part-time as an economist at Deltares – the leading Dutch knowledge institute in the field of water management – specializing in economics of climate change, with focus on floods and droughts management.
I am interested in the feedbacks between policies and aggregated outcomes of individual decisions in the context of spatial and environmental policy-making. The issue of social interactions and information diffusion through networks to affect economic behavior is highly relevant here. My research line focuses on exploring how behavioral changes at micro level may lead to critical transitions (tipping points/regime shifts) on macro level in complex adaptive human-environment systems in application to climate change economics. I use agent-based modelling (ABM) combined with social science methods of behavioral data collection on individual decisions and social networks. This research line has been distinguished by the NWO VENI and ERC Starting grants and the Early Career Excellence award of the International Environmental Modeling Society (iEMSs). In 2018 I was invited to serve as the Associate Editor of the Environmental Modelling & Software journal, where I have been a regular Member of the Editorial Board since 2013.
Klaus G. Troitzsch was a full professor of computer applications in the social sciences at the University of Koblenz-Landau since 1986 until he officially retired in 2012 (but continues his academic activities). He took his first degree as a political scientist. After eight years in active politics in Hamburg and after having taken his PhD, he returned to academia, first as a senior researcher in an election research project at the University of Koblenz-Landau, from 1986 as full professor of computer applications in the social sciences. His main interests in teaching and research are social science methodology and, especially, modelling and simulation in the social sciences.
Among his early research projects there is the MIMOSE project which developed a declarative functional simulation language and tool for micro and multilevel simulation between 1986 and 1992. Several EU funded projects were devoted to social simulation and policy modelling, the most recent from 2012 to 2015 combining data/text mining and agent-based simulation to analyse the global dynamics of extortion racket systems.
He authored, co-authored, and co-edited several books and many articles in social simulation, and he organised or co-organised a number of national and international conferences in this field. Over nearly three decades he advised and/or supervised more than 55 PhD theses, most of them in the field of social simulation. He offered annual summer and spring courses in social simulation between 1997 and 2009; more recent courses of this kind are now being organised by the European Social Simulation Assiciation and held at different places all over Europe (mostly with his contributions).
Computational social science, structuralist theory reconstruction
1987-1989: assistant professor at the Neuchâtel University (Switzerland)
1990-2001: full professor at the Neuchâtel University (Switzerland): artificial intelligence & software engineering
2001- : senior researcher at CIRAD in the unit “Gestion des Ressources et Environnement” (GREEN) and from 2021 “Savoirs ENvironnement Sociétés” (UMR SENS)
Former professor at the University of Neuchatel in Switzerland and now senior researcher at CIRAD in France, I am doing research on artificial intelligence since 1984. Having begun with logic programming, I naturally applied logics and its extensions (i.e. modal logics of various sorts) to specify agent behaviour. Since 1987, I moved both to embedded intelligence (using mobile robots) and multi-agent systems applied, in particular, to job-shop scheduling and complex system simulation and design. Since 2001, I exclusively work on modelling and simulation of socio-ecosystems in a multidisciplinary team on renewable resources management (GREEN). I am focusing on modelling complex systems in a multi-disciplinary (economist, agronomist, sociologists, geographers, etc.) and multi-actor (stakeholders, decision makers) setting. It includes:
- representing multiple points of view at various scales and levels on a complex socio-ecosystem, using ontologies and contexts
- representing the dynamics of such systems in a variety of formalisms (differential equations, automata, rule-based systems, cognitive models, etc.)
- mapping these representations into a simulation formalism (an extension of DEVS) for running experiments and prospective analysis.
This research is instantiated within a modelling and simulation platform called MIMOSA (http://mimosa.sourceforge.net). The current applications are the assessment of the sustainability of management transfer to local communities of the renewable ressources and the dynamics of agro-biodidversity through networked exchanges.
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.
I am a computational archaeologist with a strong background in humanities and social sciences, specialising in simulating socioecological systems from the past.
My main concern has been to tackle meaningful theoretical questions about human behaviour and social institutions and their role in the biosphere, as documented by history and archaeology. My research focuses specifically on how social behaviour reflects long-term historical processes, especially those concerning food systems in past small-scale societies. Among the aspects investigated are competition for land use between sedentary farmers and mobile herders (Angourakis et al. 2014; 2017), cooperation for food storage (Angourakis et al. 2015), origins of agriculture and domestication of plants (Angourakis et al. 2022), the sustainability of subsistence strategies and resilience to climate change (Angourakis et al. 2020, 2022). He has also been actively involved in advancing data science applications in archaeology, such as multivariate statistics on archaeometric data (Angourakis et al. 2018) and the use of computer vision and machine learning to photographs of human remains (Graham et al. 2020).
As a side, but not less important interest, I had the opportunity to learn about video game development and engage with professionals in Creative Industries. In one collaborative initiative, I was able to combine my know-how in both video games and simulation models (\href{https://doi.org/10.1007/978-3-030-92843-8_15}{Szczepanska et al. 2022}).
As of my incorporation into the Department of Computer Architecture and Operating Systems of the UAB as a postgraduate student, it is possible to divide my scientific-technical career into the following stages:
Simulation of Parallel Applications (1992-99): Focused on the design and development of simulators of parallel applications. This research main objective was the definition of abstractions for parallel programs, based on characterizing tasks and their dependences. Two main abstractions were developed, at first a simpler one, which was easier to parametrize, and, next, a more complex an accurate one. Using these characterizations, several simulation tools were programmed and used in the context of national and European projects. As part of my Master’s thesis, I was involved in the design and development of some of these simulation applications.
National projects: 4, European: 2
International conferences: 3, National: 1, Journal papers: 3
Security in Distributed Systems (2007-12): Focused on the design and development of the FPVA (First Principles Vulnerability Assessment) methodology for the evaluation of vulnerabilities in Grid applications. This methodology clearly defined a set of steps for the assessment of Grid applications vulnerabilities, most of these steps could be automatized or at least supported by specific tools. Jointly with other professors of our group and from the University of Wisconsin, I was involved in the original definition and application of this methodology.
International projects: 2
Master Thesis: 1, Ph.D. Thesis: 1
International conferences: 2, National: 1, Journal papers: 2
Parallel Application Modeling (1999-present): This is my main line of research, aimed at defining high-level performance models for parallel applications. Initially, models were defined for MPI applications with a master-worker and pipeline structure, but later this line has been expanded with the definition of models for memory-intensive OpenMP applications, composed (mix of several structures) applications, applications based on mathematical libraries, distributed data-intensive applications and, finally, applications based on the simulation of agents (ABS) with SPMD structure.
As a result of the work on modeling the performance of ABS parallel systems, we have opened a new line for the definition and implementation of a benchmark for assessing the performance of the parallel simulators generated by well-known platforms, such as FLAME, Repast-HPC or D-Mason. In addition, the knowledge we have gained on this topic has opened new ways of collaboration for optimizing real parallel ABS in the health sciences area (tumor growth and infection spread).
National projects: 12, European: 1
International conferences: 17, National: 4, Journal papers: 11
International Presentations: 4
Parallel Applications Tuning Tools (2010-present): Focused on the design and development of tools for automatic tuning and, in some cases, also dynamic tuning of parallel applications. These tools allow the integration of performance models in the form of external components provided by the analyst. For this reason, this research line is tightly coupled with the Parallel Application Modeling one. The two main tools developed totally or partially by our group are Monitoring Analysis and Tuning Environment-MATE (and its highly scalable evolution ELASTIC) and Periscope Tuning Framework-PTF.
National projects: 2, European: 1
International conferences: 11, Journal papers: 2
Tools: MATE, ELASTIC, PTF
International Presentations: 5
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