Displaying 10 of 73 results for "Hans-Joerg Althaus" clear search
Peter Gerbrands is a Post-Doctoral Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure for FIRMBACKBONE. He teaches data science courses: “Applied Data Analysis and Visualization” and “Introduction to R”. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In Fall 2023, he is a Visiting Research Scholar at SUNY Binghamton in NY.
agent-based simulations
social network analysis
complex systems
big data analysis
statistical learning
computational social science
Dr. Saeed Moradi received his Ph.D. in Civil Engineering from Texas Tech University in Lubbock, Texas. Saeed has 11+ years of experience in research, policymaking, housing sector, construction management, and structural engineering. His career developed his enthusiasm for the enhancement of post-disaster recovery plans. Through his research on disaster recovery, community resilience, and human-centered complex systems, Saeed aims to bridge the gap between social sciences and civil/infrastructure engineering.
Community and Infrastructure Resilience
Disaster Recovery
Complex Systems Modeling
Agent-Based Modeling
System Dynamics
Machine Learning
Pattern Recognition
Data Mining
Spatial Analysis and Modeling
Construction Management
Building Information Modeling
Amin is a PhD student in the quantitative and systems biology graduate program at UC Merced. He has been passionate about entrepreneurship since his undergraduate years in his hometown of Isfahan and then later in Bologna, Italy, where he completed his masters. Once a recipient of the Innovators Under 35 Award in Italy, he believes there is massive opportunity for society to train and motivate younger minds to acquire an entrepreneurial mindset, along with entrepreneurship skills.
Entrepreneurship, management, mathematical modeling, agent based modeling.
Tarik Hadzibeganovic is a complex systems researcher and cognitive scientist interested in all challenging topics of mathematical and computational modeling, in both basic and applied sciences. His particular focus has been on several open questions in evolutionary game theory, behavioral mathematical epidemiology, sociophysics, network theory, and episodic memory research. When addressing these questions, he combines mathematical, statistical, and agent-based modeling methods with laboratory behavioral experiments and Big Data analytics.
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
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
Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.
I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.
While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.
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