About

Welcome to EUROSIM 2026!

Dear Sir/Madam,

Innovations and improvements are required to react quickly to the new trends of the global economy. Over the years, Modeling & Simulation (M&S) has proved to be one of the most effective, beneficial and successful methodologies to investigate and study complex systems belonging to various sectors/areas. Today, the emergence of Artificial Intelligence (AI) is transforming this landscape, offering unprecedented opportunities to enhance model fidelity, accelerate simulation speed, enable autonomous decision-making, and unlock new paradigms in digital twins and predictive analytics. Nevertheless, to take full advantage of these synergies, researchers and practitioners face significant challenges: ensuring transparency and trust in AI-enhanced models, bridging the gap between data-driven and physics-based approaches, and integrating cutting-edge algorithms into real-world decision support systems. Addressing these opportunities and challenges will define the next generation of M&S applications.

M&S combined with AI is now widely applied in many domains, from industry to social sciences, from logistics to military, from energy to healthcare, providing a truly multidisciplinary perspective where theory, data, and learning algorithms work together to generate deeper insights and more robust solutions.

The 2026 Federation of European Simulation Societies’ Congress will be a unique platform for knowledge exchange, debate, and collaboration on these themes. Scientists, researchers, decision makers, practitioners, and students will come together to review theoretical advances, present research results, and share industrial experiences under the banner of “M&S & AI: Opportunities and Challenges for Present & Future.”

We warmly invite you to take an active part in this congress and the co-located events to be held in Genoa, Italy, in September 2026, and join us in exploring the exciting future of multidisciplinary M&S empowered by AI.

Sincerely,
EUROSIM 2026 Organization Committee

Topics & Tracks

Authors are kindly invited to include in their papers and presentations all the research works, case studies and application both theoretical and applied. Topics of interests include the following topics, however different ones concerning Modeling & Simulation in Industry are welcome.

Topics

  • Agent-Based Simulation
  • System Dynamics Simulation
  • Discrete Event Simulation
  • Supply Chain Management, Logistics & Transportation
  • Industrial Case Studies Complex, Intelligent, Adaptive and Autonomous Systems (CIAAS)
  • Environment and Sustainability Applications
  • Data Science for Simulation
  • Artificial Intelligence
  • Agentic AI and Simulation
  • Military Application
  • Hybrid Simulation
  • Manufacturing Applications
  • Simulation-Optimization
  • Tutorials/workshops from academics and industry, PhD Track and many more…

Tracks

An Open Track addresses specific, well-defined subjects and has no upper limit on the number of papers that can be submitted to it. Contributions to open tracks can be either regular papers or short papers (min 3 pages length) and they will appear in the conference proceedings. The organizer(s) of an Open Track will be inviting contributions but the tracks are open to everyone is willing to contribute. If at least 4 papers are submitted to the track, one (or more) Invited Sessions, including those papers, will be part of the conference program.

Co-Chairs: 

Lin Zhang (a), Beihang University, johnlin9999@163.com

Chun Zhao (a), Beijing Information Science and Technology University, zhaochun@bistu.edu.cn

Qinglei Ji (b), Volvo Cars Corporation, qinglei_ji@outlook.com

Affiliation: (a) Beihang University (China), (b) Volvo Cars Corporation (China)

Track Description:

This Track of Federation of European Simulation Societies’ Conference (EUROSIM 2026) aims at presenting Research and Development devoted to system engineering.

Model-Based Systems Engineering (MBSE) has become a End-to-end methodology for addressing the systems’ complexity across their entire DevOps lifecycle. Recently, the increasing scale and interdependence of system models pose new challenges with respects to automation, explainable, optimization, etc.

Artificial Intelligence (AI), with its rapid advancements in machine learning, natural language processing, knowledge representation, and reasoning, offers transformative potential for enhancing MBSE. Integrating AI with MBSE can enable intelligent model generation, automated requirements analysis, predictive system behavior modeling, adaptive lifecycle management, etc.

This Track aims to promote academic research, technology development, and industrial applications at the intersection of AI and MBSE. Related concepts, methods, methodologies as well as innovative models, solutions and simulators and related case studies and challenges are invited to submit their original contributions. Topics include, but are not limited to:

  • Modeling and simulation language
  • AI-Driven Modeling and Automation
  • Develop intelligent methods and tools
  • Learning and Optimization in MBSE
  • Intelligent Lifecycle Management
  • Natural Language and Human–System Interaction
  • Industrial Applications and Case Studies
  • Foster cross-disciplinary applications
  • Verification, Validation and Accreditation of MBSE

Co-Chairs: 

Fabio De Felice (a), Università degli Studi di Napoli “Parthenope”,  fabio.defelice@uniparthenope.it

Antonella Petrillo (a), Università degli Studi di Napoli “Parthenope” , antonella.petrillo@uniparthenope.it

Affiliation: (a) Università degli Studi di Napoli, “Parthenope”(Italy)

Track Description:

This track focuses on the role of modeling and simulation as key enablers for innovation, efficiency, and sustainability in modern manufacturing systems. With the increasing adoption of Industry 4.0 and Industry 5.0 paradigms, manufacturing environments are becoming highly interconnected, data-driven, and adaptive. Advanced simulation approaches are essential to design, analyze, optimize, and control such complex systems across their entire lifecycle. The track welcomes contributions addressing theoretical advances, methodological developments, and industrial applications of modeling and simulation in manufacturing. Topics of interest include discrete-event, continuous, hybrid, and agent-based simulation; digital twins; AI-enhanced simulation; and data-driven and physics-based models. Particular attention is given to applications supporting smart manufacturing, resilient production systems, energy efficiency, sustainability, and human-centric manufacturing. Both academic and industrial contributions are encouraged, including case studies, validation studies, and real-world implementations that demonstrate the practical impact of simulation technologies on manufacturing decision-making and performance.

  • Modeling and simulation of manufacturing systems
  • Discrete-event and hybrid simulation for production systems
  • Digital twins for manufacturing and production lines
  • Simulation-based optimization and decision support
  • AI, machine learning, and data-driven simulation in manufacturing
  • Cyber-physical production systems modeling
  • Human-centric and collaborative manufacturing simulation
  • Energy-aware and sustainable manufacturing models
  • Resilience and robustness analysis of production systems
  • Supply chain and manufacturing network simulation
  • Real-time simulation and control of manufacturing processes
  • Simulation for additive and advanced manufacturing technologies
  • Verification, validation, and uncertainty quantification
  • Scalability, and integration of simulation solutions in industrial environments
  • Industrial case studies and best practices

Chair: 

Mohammad Dehghani (a), Northeastern University, m.dehghani86@gmail.com

Affiliation: (a) Northeastern University(USA)

Track Description:

The integration of simulation and artificial intelligence represents a powerful convergence with transformative potential for modeling, analysis, and decision-making in complex systems. This track welcomes all simulation paradigms including discrete event systems, Monte Carlo methods, agent-based modeling, and system dynamics, combined with AI and intelligent systems. We particularly encourage work on machine learning-based models, deep learning with simulation, reinforcement learning applications, and generative AI integration. Topics include AI-enhanced simulation automation, intelligent scenario generation, surrogate modeling, and simulation-driven AI training and validation. The track seeks contributions spanning practical applications in manufacturing, healthcare, supply chain management, and beyond, as well as theoretical frameworks that open new pathways for integrating these complementary technologies to advance our understanding and optimization of complex systems.

Generative AI & Emerging Paradigms:

  • Generative AI for simulation model creation and synthetic data generation
  • Large Language Models (LLMs) for simulation design and automation
  • Agentic AI systems and autonomous simulation workflows
  • Multi-agent coordination and Agent-to-Agent (A2A) communication in simulations
  • Foundation models for domain-specific simulation applications

Classical AI & Machine Learning:

  • Machine learning-based metamodeling and surrogate models
  • Reinforcement learning for simulation optimization and control
  • Deep learning for pattern recognition and prediction in simulation outputs
  • Neural networks for system identification and model calibration
  • Intelligent optimization and automated parameter tuning

Integration & Applications:

  • Digital twins powered by AI and simulation
  • AI-driven simulation in manufacturing, healthcare, and supply chain management
  • Simulation environments for AI training, testing, and validation
  • Theoretical frameworks for AI-simulation integration and convergence
  • Teaching and training methodologies for AI-integrated simulation in academic settings
  • Educational frameworks and curriculum development for simulation and AI convergence

Co-Chairs: 

Oliver Rose (a), University of the Bundeswehr Munich, oliver.rose@unibw.de

Tobias Uhlig (a), University of the Bundeswehr Munich, tobias.uhlig@unibw.de

Affiliation: (a) University of the Bundeswehr Munich

Track Description:

The Military Applications Track is interested in papers that describe the application of modeling and simulation theory, techniques, tools and technologies to challenges in the military and national security domain. Example application areas include: battle management command and control, air and missile defense, campaign analysis, weapon-target pairing, multi-domain operations, sustainment operations, operational testing and evaluation, wargaming and assessments, CBRNE defense, critical infrastructure analysis, homeland defense and domestic civil support operations, cybersecurity, information operations, electronic warfare, intelligence, surveillance and reconnaissance, medical and healthcare operations, manpower and personnel, readiness and training, cost, risk and decision analysis, special operations, etc.

  • Challenges and innovations for representation and implementation of command, control, and communications
  • Swarm intelligence
  • Cybersecurity operations / cyber threat intelligence
  • Social media analytics
  • Hardware-in-the-loop simulations
  • Human-machine teaming
  • Future platforms and weapons prototyping
  • Synthetic environments
  • Multi-sensor fusion
  • Complex behaviors of semi-automated forces
  • Electronic warfare
  • Expeditionary medical operations
  • Automatic scenario planning and experimentation
  • Multi-resolution models

Co-Chairs: 

Paolo Scala (a), KLM, Paolo.Scala@klm.com

Miguel Mujica Mota (b), Amsterdam University of Applied Sciences, m.mujica.mota@hva.nl

Affiliation: (a) KLM(Netherlands), (b) Amsterdam University of Applied Sciences(Netherlands)

Track Description:

Scope and Objectives Complex challenges in industries such as aviation, manufacturing, and service-based supply chains require sophisticated decision-making tools. Historically, these problems have been addressed through two distinct lenses: classical optimization and simulation. While optimization offers computational efficiency, it often necessitates rigid abstractions and fixed parameters. Conversely, simulation provides high-fidelity descriptions of complex systems but is limited by the sampling of the configuration space.

 

This track focuses on the growing body of research dedicated to hybrid approaches. By merging the precision of mathematical programming with the descriptive power of simulation (e.g., Simheuristics or Matheuristics), researchers can better address real-world stochasticity and complexity. We invite submissions exploring innovative methodologies and applications in areas including, but not limited to:

  • Production Planning: Scheduling and resource allocation.
  • Logistics: Routing problems and network design.
  • Service Systems: Capacity management and aviation operations. Hospital Services. Transportation Services.
  • Methodological Advances: Integration of metaheuristics with discrete-event or agent-based simulation.

Co-Chairs: 

Natalia Jimenez (a), Universidad Pablo de Olavide, njimjim@upo.es

Lara Ezquerra (a), Universidad de las Islas Baleares, Lezquerra001@gmail.com

Affiliation: (a) Universidad Pablo de Olavide(Spain)

Track Description:

This track focuses on how Modelling & Simulation (M&S) and Artificial Intelligence (AI) jointly advance the understanding and governance of human behaviour in complex social systems. We welcome contributions that integrate agent-based modelling, multi-agent systems, computational social science, and AI/ML methods to analyse behaviour, interaction, and emergent phenomena, as well as to support decision-making and policy design. Topics include AI-assisted model development (e.g., automated calibration, surrogate modelling, generative agents), data-driven and hybrid approaches combining simulation with experiments or observational data, and the use of AI to improve validation, uncertainty quantification, and scenario exploration. We particularly encourage work that addresses challenges at the M&S–AI interface: transparency and interpretability, robustness and bias, reproducibility, ethical and responsible use, and the reliability of AI-generated behaviours in simulation. Applied papers are welcome across domains such as sustainability, public policy, health, organisations, markets, mobility, and digital platforms.

  • AI-enhanced agent-based modelling and multi-agent simulation
  • Generative agents and LLM-based behavioural modelling: opportunities and limitations
  • ML for calibration, validation, parameter estimation and model discovery
  • Surrogate modelling / emulators to accelerate simulation and optimisation
  • Data-driven & hybrid M&S (simulation + experiments/surveys/administrative/big data)
  • Uncertainty quantification, sensitivity analysis and robust decision-making with AI
  • Explainable and interpretable AI for behavioural simulation (XAI for M&S)
  • Bias, fairness and ethics in AI-driven simulations and synthetic populations
  • Human-AI interaction and socio-technical systems in simulation contexts
  • Behavioural change, social influence, norms and collective dynamics under AI tools
  • Network, spatial and mobility processes with AI-supported inference
  • Simulation-based policy evaluation and AI-assisted scenario generation
  • Reproducibility, open models, benchmarking, and verification in M&S & AI
  • Trust, accountability and governance of AI-enabled M&S
  • Applications: climate/sustainability, public health, organisations, markets, platforms

Chair: 

Yunbae Kim, kimyb@skku.edu

Affiliation: SUNGKYUN KWAN UNIVERSITY(SKKU) – College of Engineering – System Management Engineering, Seoul, Korea

Track Description:

In this track, we present recent advancements in analyzing and understanding the spread of pandemic diseases using a variety of simulation techniques, including agent-based simulation, discrete event simulation, system dynamics, and differential equation–based models.

These approaches and the results should provide critical insights into how diseases propagate in our highly interconnected world and are essential for improving preparedness, response strategies, and policy-making for future pandemics. We also welcome the feedbacks on Covid-19.

Key Dates

Paper Submission Deadlines

  • Special Session/Open Track Proposal Closure: April 10th, 2026
  • Draft Paper Submission Deadline: April 15th, 2026
  • Notification of Acceptance & Review Reports: May 15th, 2026
  • Camera-ready Paper Submission Deadline: June 15th, 2026

Registration Deadlines

  • Early Bird Registration Closure: July 24th, 2026
  • Late Registration Closure: August 31st, 2026

Committees


Agostino Bruzzone

In memoriam of Professor Agostino G.Bruzzone
EUROSIM Honorary General Chair
University of Genoa, Italy


Francesco Longo

EUROSIM 2026 General Co-Chair
University of Calabria, Italy


Marco Gotelli

EUROSIM 2026 Program Co-Chair
University of Genoa, Italy


miguel mujica mota

EUROSIM 2026 Programm Co-Chair
Amsterdam University of Applied Sciences , Netherlands


Marina Massei

EUROSIM 2026 Conference Coordinator
University of Genoa, Italy

EUROSIM 2026 International Programm Committee

Idalia Flores – National University of Mexico, Mexico City, Mexico
Edmond Hajrizi – University for Business and Technology , Prishtina , Kosovo
Mohammad Dehghani – Northeastern University, Boston, Massachusetts, United States.
Jose Maria Ortiz-Gomez – Zayed University, Dubai, United Arab Emirates.
Cristina Ruiz Martin – Carleton University, Ottawa, Ontario, Canada.
Antonella Petrillo – University of Napoli Parthenope
Fabio de Felice – University of Napoli Parthenope
Benedikt Badanik – University of Žilina, Zilina, Slovakia
Mario L.Rus – University of Córdoba, Córdoba, in Andalusia, Spain
Christina Rott – Vrije Universiteit Amsterdam, Amsterdam, Netherlands
Vittorio Solina – DIMEG, University of Calabria, Italy

EUROSIM 2026 Organization Staff

Xhulia Sina – DIME, University of Genoa, Italy
Luca Cirillo – DIME, University of Genoa, Italy
Filippo Ghisi – DIME, University of Genoa, Italy
Simone Talarico – DIMEG, University of Calabria, Italy
Marco Vetrano – CAL-TEK S.r.l., Italy
Kirill Sinelshchikov – Simulation Team, Italy
Antonio Cimino, University of Salento, Italy
Alessio Baratta – MSC-LES, University of Calabria, Italy
Pierpaolo Veltri – MSC-LES, University of Calabria, Italy
Farshad Shamlu – DIME, University of Genoa, Italy


Vittorio Solina – DIMEG, University of Calabria, Italy
Antonio Padovano – University of Calabria, Italy
Letizia Nicoletti – CAL-TEK S.r.l., Italy
Mohaiad Osman Elbasheer – MSC-LES, University of Calabria, Italy
Cataldo Russo – CAL-TEK S.r.l., Italy
Caterina Fusto – MSC-LES, University of Calabria, Italy
Alessandro Chiurco – DIMEG, University of Calabria, Italy
Virginia D’Augusta – DIMEG, University of Calabria, Italy
Karen Althea Manfredi – MSC-LES, University of Calabria, Italy
Antonio Nervoso – MSC-LES, University of Calabria, Italy

Local Organizing Committee

Bharath Kumar Gadupuri – DIME, University of Genoa, Italy
Xhulia Sina – DIME, University of Genoa, Italy
Luca Cirillo – DIME, University of Genoa, Italy
Filippo Ghisi – DIME, University of Genoa, Italy
Giovanni M.Ferraris – DIME, University of Genoa, Italy
Marco Gotelli – DIME, University of Genoa, Italy
Marina Massei – DIME, University of Genoa, Italy
Kirill Sinelshchikov – Simulation Team, Italy
Farshad Shamlu – DIME, University of Genoa, Italy

Get on board the team now!

Are you willing to join the Organization Committee or the International Program Committee? Discover the benefits and opportunities now and submit your proposal to f.longo@unical.it, i3m@msc-les.org

Fill the form!

Do you want to become an EUROSIM 2026 Partner or Sponsor?

EUROSIM Partnership and Sponsorship Opportunities are an excellent way to increase significantly your organization’s or institution’s visibility, to deliver a personal message and demonstrate your support to the Multidisciplinary Modeling and Simulation community. Are you willing to become an EUROSIM Scientific Partner? Are you an Industrial Organization that is planning to support EUROSIM? Are you a Publisher, Editor, Journal or Magazine? Please contact f.longo@unical.it and massei@itim.unige.it for more information!

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