Call for Papers

ACM Transactions on Modeling and Computer Simulation (TOMACS)

Special Issue on: Simulation in the Age of Digital Twins and AI

Guest Editors

Hong Wan, North Carolina State University ([email protected])

Sara Shashaani, North Carolina State University ([email protected])

Philipp Andelfinger, Nanyang Technological University ([email protected])

Overview

Advances in artificial intelligence and digital twin technologies are fundamentally reshaping simulation research. From learning-augmented stochastic systems to real-time, data-driven replicas of complex processes, simulation is evolving into an integrated computational framework that interacts dynamically with AI, data assimilation, and adaptive decision-making systems.

This Special Issue of ACM TOMACS seeks original contributions at the computational and theoretical frontiers of simulation, AI, and digital twin systems.

Scope and Themes

All submissions must demonstrate substantive integration of AI and/or digital twin components within simulation research. Pure simulation contributions without meaningful AI or digital twin elements are outside the scope of this issue.

We welcome contributions that advance simulation research through, or in service of, AI-enabled and digital twin systems, including but not limited to:

AI-Supported Simulation Modeling

• Generative models for simulation and synthetic data generation
• LLM-enhanced simulation modeling and calibration
• Data-driven metamodeling and surrogate construction
• Rule and process mining for simulation modeling

AI-Integrated Simulation

• Learning-augmented stochastic simulation
• Reinforcement learning combined with simulation
• LLM-based reasoning over simulations
• AI-guided sampling and rare-event simulation
• Differentiable simulators and models

Digital Twin–Driven Simulation

• Computational architectures for AI-enabled digital twins
• Hybrid physics-informed and data-driven digital twin models
• Real-time model updating and adaptive simulation
• Scalable digital twin infrastructures and distributed systems
• Large-scale parallel and distributed simulation for digital twins

Inference and Uncertainty in AI-Simulation Systems

• Simulation-based inference
• Data assimilation and state estimation
• Uncertainty quantification in AI-enabled systems
• Robust and trustworthy AI-driven simulation frameworks

Computational and Theoretical Foundations

• AI-enhanced simulation optimization
• Simulation on AI accelerators
• Cloud-native simulation workflows

Submissions should advance foundational computational methodologies, theoretical guarantees, scalable architectures, or integrative frameworks that define the next generation of AI-enabled simulation systems.

Submission Guidelines

Manuscripts must follow ACM TOMACS author guidelines and submission policies. All submissions will undergo rigorous peer review consistent with ACM TOMACS standards.

Submissions based on prior workshop presentations must represent a substantial extension beyond any previously published or publicly available version.

Please submit through the ACM TOMACS manuscript system and select Special Issue: Simulation in the Age of Digital Twins and AI during submission.

Important Dates

• Submission deadline: September 30, 2026
• First decision: January 15, 2027
• Revision due: March 30, 2027
• Final decision: June 15, 2027
• Tentative publication: September 2027

Vision

Simulation is entering a transformative era. As AI reshapes computational science and digital twins bridge the gap between models and physical reality, the boundaries of what simulation can represent, predict, and optimize are expanding rapidly. This Special Issue aims to capture the foundational advances that will define simulation methodology for the decades ahead.

We invite researchers worldwide to contribute work that pushes the theoretical and computational boundaries of simulation in the age of digital twins and AI.

Journal of Simulation

Special Issue on: Simulation in the New Age of Digital Twins,  AI, and Quantum Computing

Guest Editors

Sara Shashaani, North Carolina State University ([email protected])

Enlu Zhou, Georgia Institute of Technology ([email protected])

Overview and Scope

Advances in artificial intelligence (AI), digital twin, and quantum computing technologies are fundamentally reshaping simulation research. From learning-augmented stochastic systems to real-time, data-driven replicas of complex processes, simulation is evolving into an integrated computational framework that interacts dynamically with AI, data assimilation, and adaptive decision-making systems. This Special Issue of Journal of Simulation (JoS) seeks original contributions in theory, computation, and applications of simulation integrated with AI, digital twin systems, and/or quantum computing.

Please note that this call is open to the public, not restricted to the workshop participants.

Submission Guidelines

Manuscripts must follow JoS author guidelines and policies and will undergo expedited peer review. Please submit through the JoS submission system via www.tandfonline.com/tjsm and select Special Issue: 2026 I-SIM Workshop during submission.

Important Dates

• Submission deadline: November 30, 2026
• First decision: February 15, 2027
• Revision due: April 15, 2027
• Final decision: June 15, 2027
• Tentative publication: September 2027