Displaying 10 of 64 results policy clear search
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.
I am a Reader in the Centre for Health Economics, conducting interdisciplinary research aimed at tackling healthcare challenges and improving decision-making and implementation in healthcare policy. My research is centred around using systems thinking and modelling approaches in health economics evaluation and draws on tools and methods from mathematical epidemiology, economics, management science, and computer science, among other fields.
My main body of work involves systems modelling and simulation, and it involves integrating disease and economic models for policy impact evaluation and prioritisation. I am interested in both infectious disease and non-communicable disease modelling. From a methodological standpoint, I am particularly interested in strengthening rigour in agent-based modelling and hybrid models, which integrate modelling methods when this simplifies analyses. I have applied my research to studying and conducting knowledge-exchange activities addressing global health challenges. This includes conducting healthcare intervention and policy evaluations, studying health systems strengthening in low- and middle-income countries, studying antimicrobial resistance policy globally and in the UK, evaluating COVID-19 policy and interventions, investigating how behaviour and social structure affect health and diseases, and exploring the role of incentives in healthcare policy design.
I hold a PhD in Management Science, specialising in modelling for healthcare policy, from the University of Strathclyde and an MA in economics and BA honours economics from McGill University, in Montreal.
Dr. Kimberly G. Rogers studies the coupled human-natural processes shaping coastal environments. She obtained a B.Sc. in Geological Sciences from the University of Texas at Austin and began her graduate studies on Long Island at Stony Brook University’s School of Marine and Atmospheric Sciences. Rogers completed her Ph.D. at Vanderbilt University, where she specialized in nearshore and coastal sediment transport. She was a postdoctoral scholar and research associate at the Institute for Arctic and Alpine Research at the University of Colorado Boulder. In 2014, her foundation in the physical sciences was augmented by training in Environmental Anthropology at Indiana University Bloomington through an NSF Science, Engineering, and Education for Sustainability (SEES) Fellowship.
Rogers’s research is broadly interdisciplinary and examines evolving sediment dynamics at the land-sea boundary, principally within the rapidly developing river deltas of South Asia. As deltas are some of the most densely populated coastal regions on earth, she incorporates social science methods to examine how institutions — particularly those governing land use and built infrastructure — influence the flow of water and sediment in coastal areas. She integrates quantitative and qualitative approaches in her work, such as direct measurement and geochemical fingerprinting of sediment transport phenomena, agent-based modeling, institutional and geospatial analyses, and ethnographic survey techniques. Risk holder collaboration is an integral part of her research philosophy and she is committed to co-production and capacity building in her projects. Her work has gained recognition from policy influencers such as the World Bank, USAID, and the US Embassy Bangladesh and has been featured in popular media outlets such as Slate and Environmental Health Perspectives.
Topics:
Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Resource scarcity
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Sustainable Development
Methods:
Agent-Based-Modeling
Genetic algorithms
Evolutionary economics
Behavioural economics
Ecological economics
Complexity Theory
Lu Ping is a dedicated researcher in interdisciplinary fields including artificial intelligence (AI), digital economy, technological innovation, and industrial economics. Currently serving as an Associate Research Fellow at the China Academy of Information and Communications Technology (CAICT), Lu Ping focuses on examining the impacts of digital technologies (e.g., AI, big data, and IoT) on economic growth, industrial ecosystems, policy formulation, and societal ethics through multidimensional data modeling and empirical research.
Representative Academic Contributions:
1. AI Development and Societal Implications
A Brief History of Artificial Intelligence Development in China (2017): Explored the technological evolution and policy-driven pathways of China’s AI industry.
Ethical Dilemmas Faced by AI Algorithms (2018): Analyzed ethical challenges such as algorithmic bias and data privacy, proposing governance frameworks.
A Brief History of the Evolution of Smart Hardware in China (2018): Systematically reviewed the technological iterations and market dynamics of China’s smart hardware sector.
2.Technological Innovation and Industrial Economics
An Empirical Analysis of Technological Innovation Driving Growth in Internet Companies: Evidence from A-Share Listed Internet Firms in Shanghai and Shenzhen (2019).
Research on Competitiveness Measurement of Frontier Emerging Industries Based on Data Envelopment Analysis (DEA) Models (2019).
3.Digital Economy and Market Behavior
Correlation Analysis of Crowdfunding Behavior and Funding Performance for Internet Products: A Bayesian Approach Based on JD.com Crowdfunding Data (2018): Uncovered nonlinear relationships between user participation and project success rates using crowdfunding platform data.
Analyzing the Effects of Developer and User Behavior on Mobile App Downloads (2019): Built predictive models for app market performance based on user behavior data.
4.Policy Simulation
General Equilibrium Analysis of Beijing’s Water Supply and Consumption Policies: A Computable General Equilibrium (CGE) Model-Based Approach (2015).
Impact Analysis of EU Food Safety Standards on China’s Food Industry: A Dynamic Global Trade Analysis Project (GTAP) Model-Based Study (2015).
Academic Contributions:
Pioneered interdisciplinary paradigms in industrial economics research by integrating perspectives from econometrics, data science, and sociology. Published high-impact research in AI ethics, digital economy policies, and resource-environmental economics, providing decision-making references for academia and policymakers.
My research focuses on the interdisciplinary nexus of artificial intelligence (AI), digital economy, technological innovation, and industrial economics, with an emphasis on understanding how digital technologies reshape economic structures, policy frameworks, and societal norms. Key areas of interest include:
Matteo Richiardi is an internationally recognised scholar in micro-simulation modelling (this includes dynamic microsimulations and agent-based modelling). His work on micro-simulations involves both methodological research on estimation and validation techniques, and applications to the analysis of distributional outcomes, the functioning of the labour market and welfare systems. He is Chief Editor of the International Journal of Microsimulation. Examples of his work are the two recent books “Elements of Agent-based Computational Economics”, published by Cambridge University Press (2016), and “The political economy of work security and flexibility: Italy in comparative perspective”, published by Policy Press (2012).
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.
I studied Mathematics at Oxford (1979-1983) then did youth work in inner city areas for the Educational Charity. After teaching in Grenada in the West Indies we came back to the UK, where the first job I could get was in a 6th form college (ages 16-18). They sent me to do post16 PCGE, which was so boring that I also started a part-time PhD. The PhD was started in 1992 and was on the meaning and definition of the idea of “complexity”, which I had been pondering for a few years. Given the growth of the field of complexity from that time, I had great fun reading almost anything in the library but I did finally finish it in 1999. Fortunately I got a job at the Centre for Policy Modelling (CfPM) in 1994 with its founder and direction, Scott Moss. We were doing agent-based social simulation then, but did not know it was called this and did not meet other such simulators for a few years. With Scott Moss we built the CfPM into one of the leading research centres in agent-based social simulation in the world. I became director of the CfPM just before Scott retired, and later became Professor of Social Simulation in 2013. For more about me see http://bruce.edmonds.name or http://cfpm.org.
All aspects of social simulation including: techniques, tools, applications, philosophy, methodology and interesting examples. Understanding complex social systems. Context-dependency and how it affects interaction and cognition. Complexity and how this impacts upon simulation modelling. Social aspects of cognition - or to put it another way - the social embedding of intelligence. Simulating how science works. Integrating qualitative evidence better into ABMs. And everything else.
Displaying 10 of 64 results policy clear search