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Bruno Bonté Member since: Mon, Feb 13, 2017 at 09:44 AM Full Member

PhD in Computer Science applied to Modelling and Simulation, University of Montpellier 2, Master degree in Computer Science applied to Artificial Intelligence and Decision in Paris 6 University of Pierre and Marie Curry

Master Degree

I discovered at the same time Agent-Based Modeling method and Companion Modelling approach during my master degrees (engeenering and artificial intelligence and decision) internship at CIRAD in 2005 and 2006 where I had the opportunity to participate as a modeller to a ComMod process (Farolfi et al., 2010).

PhD

Then, during my PhD in computer Science applied to Modeling and Simulation, I learned the Theory of Modeling and Simulation and the Discrete EVent System specification formalism and proposed a conceptual, formal and operational framework to evaluate simulation models based on the way models are used instead of their ability to reproduce the target system behavior (Bonté et al., 2012). Applied to the surveillance of Epidemics, this work was rather theoritical but very educative and structuring to formulate my further models and research questions about modeling and simulation.

Post-Doc

From 2011 to 2013, I worked on viability theory applied to forest management at the Compex System Lab of Irstea (now Inrae) and learned about the interest of agregated models for analytical results (Bonté et al, 2012; Mathias et al, 2015).

G-EAU

Since 2013, I’m working for Inrae at the joint The Joint Research Unit “Water Management, Actors, Territories” (UMR G-EAU) where I’m involved in highly engaging interdisciplinary researches such as:
- The Multi-plateforme International Summer School about Agent Based Modelling and Simulation (MISSABMS)
- The development of the CORMAS (COmmon Pool Resources Multi-Agents Systems) agent-based modeling and simulation Platform (Bommel et al., 2019)
- Impacts of the adaptation to global changes using computerised serious games (Bonté et al., 2019; Bonté et al. , 2021)
- The use of experimentation to study social behaviors (Bonté et al. 2019b)
- The impact of information systems in SES trajectories (Paget et al., 2019a)
- Adaptation and transformations of traditional water management and infrastructures systems (Idda et al., 2017)
- Situational multi-agent approaches for collective irrigation (Richard et al., 2019)
- Combining psyhcological and economical experiments to study relations bewteen common pool resources situations, economical behaviours and psychological attitudes.

My research is about modelling and simulation of complex systems. My work is to use, and participate to the development of, integrative tools at the formal level (based on the Discrete EVent System Specification (DEVS) formalism), at the conceptual level (based on integrative paradigms of different forms such as Multi-Agents Systems paradigm (MAS), SES framework or viability theory), and at the level of the use of modelling and simulation for collective decision making (based on the Companion Modelling approach (ComMod)). Since 2013 and my integration in the G-EAU mixt research units, my object of studies were focused on multi-scale social and ecological systems, applied to water resource management and adaptation of territories to global change and I added experimentation to my research interest, developping methods combining agent-based model and human subjects actions.

Ping Lu Member since: Fri, Feb 24, 2017 at 04:47 AM Full Member Reviewer

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:

  1. Artificial Intelligence & Digital Transformation
    Ethical and Governance Challenges of AI: Investigating algorithmic bias, data privacy, and accountability in AI systems; proposing frameworks for ethical AI development and deployment.
    AI Adoption and Economic Impact: Analyzing how AI-driven automation and innovation influence productivity, labor markets, and industrial competitiveness.
  2. Digital Economy & Platform Markets
    Crowdfunding, Sharing Economy, and Digital Platforms: Examining user behavior, market dynamics, and performance drivers in emerging digital ecosystems (e.g., crowdfunding campaigns, app markets).
    Digital Innovation and Entrepreneurship: Studying the role of technological innovation in firm growth, particularly in internet-based industries.
  3. Technological Innovation & Industrial Policy
    Innovation-Driven Industrial Competitiveness: Developing quantitative models (e.g., DEA, CGE) to assess the efficiency and competitiveness of emerging industries under technological disruption.
    Policy Evaluation and Simulation: Using computational modeling to analyze the economic and industrial impacts of trade policies, environmental regulations, and technological standards.
  4. Resource Economics & Sustainable Development
    Water Resource Management and Policy: Evaluating the economic and environmental trade-offs of water conservation policies through general equilibrium modeling.
    Global Trade and Food Security: Assessing the impacts of international trade regulations (e.g., food safety standards) on domestic industries and global supply chains.
  5. Cross-Disciplinary Methodological Innovation
    Integrating econometrics, data science, and behavioral economics to enhance the rigor and relevance of industrial and policy research.
    Leveraging big data analytics, machine learning, and agent-based modeling to uncover complex relationships in digital markets and technological ecosystems.

Tika Adhikari Member since: Fri, Jan 20, 2012 at 08:30 PM Full Member

Ph D, Student

Development of spatial agent-based models to sustainability science and ecosystem service assessment, integration of agent-based model with biophysical process based model, improvement of theory of GIScience and land use change science, development of spatial analytical approach (all varieties of spatial regression), spatial data modeling including data mining, linking processes such as climate change, market, and policy to study patterns.

Flavio Diniz Member since: Sun, Nov 15, 2020 at 02:10 PM

Eletronic Engineer with specialization in Computer Science and a passion for Artificial Intelligence, Simulation, Programming, and many other tech topcis . One life is really not enough to learn and experiment all cool things that are out there. Love also learning languages: Portuguese, English, French, Italian, and German.

  • Agent-based Modeling
  • Automated Planning and Distributed Problem Solving
  • Natural Language Processing
  • Machine Learning
  • Internet of Things and Cloud-based Distributed Architectures

Yao Tong Member since: Fri, Jul 19, 2024 at 02:03 AM

M.A., Sociology, Renmin University of China, B.Sc., Statistics, Central University of Finance and Economics

Computational Social Science, Social Simulation, Innovative Methods, Agent-based Modelling, Serious game
Future Studies, AI Sociology, Societal Change, and some classical sociological topics (e.g. Social Mobility and Unequality, Education, Collective Action)

Tarik Hadzibeganovic Member since: Tue, Aug 09, 2022 at 06:09 PM

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.

Tramadol Care Member since: Tue, Mar 24, 2026 at 05:41 AM Full Member

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Lukas Heck Lukas Heck Member since: Tue, Sep 20, 2022 at 04:11 PM

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Muhammad Indra Al Irsyad Member since: Wed, Nov 22, 2017 at 08:18 AM Full Member

Master degree, PhD candidate

My research examines the most effective and efficient policies for renewable energy development using an approach that integrates input-output analysis, life cycle analysis, econometric, and agent-based modelling to estimate the impacts of the policies to economic, emission, extracted materials, renewable energy capacity and social acceptance.

Hassan Bashiri Member since: Tue, Apr 28, 2015 at 06:11 AM Full Member Reviewer

PhD

I am an assistant professor in the Department of Computer Science at the Hamedan University of Technology, Hamedan, IRAN. I have completed my Ph.D. in Futures Studies (foresight) as an interdisciplinary field, an intersection of social sciences and engineering. My
background comes from computer science. For my Ph.D., I decided to pursue my education in Futures Studies; the field I thought I could apply engineering principles such as requirements engineering, analytical skills, design, modeling, planning, and, test engineering to shape the
desired futures. In PhD, I started the complex systems research field and agent-based modeling with NetLogo. In addition to several publications of papers, I published a book on complex systems titled “Futures Studies in Complex Systems” which was awarded as the book of the year by the Iranian Foresight Association.

Since May 2021, I started a research collaboration with TISSS Lab at the Johannes Gutenberg University Mainz as a project coordinator, the German Research Centre for AI, Human-Centered Multimedia, and the Centre for Research in Social Simulation. The project title is “AI for Assessment” and its objective is to understand the status quo and the future options of AI-based social assessment in public service provisions to help in the creation of improved AI technology for social welfare systems.

On the executive side, I have also various experiences, including head of the department, deputy of the Technology Incubator Center, director of university’s research affairs, and head of the International Scientific Cooperation Office.

Complex Systems, Social Modeling and Simulation
Engineering the Futures

Displaying 10 of 98 results for "Ali Termos" clear search

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