About

The ACM SIGSIM PADS conference focuses on cutting-edge research at the intersection of Computer Science and Modeling and Simulation (M&S). High-quality papers are solicited in all aspects of M&S. This year brings about fresh changes, including the introduction of thematic tracks and a two-phase submission process, ensuring a more diversified and comprehensive participation.

Topics

We encourage submissions that align with the tracks, especially the emerging topics which offer a novel focus for the year. The topics of the tracks are not considered comprehensive: we accept high-quality papers on all aspects of M&S.

Regular Tracks

1. Simulation algorithms and infrastructure — Track Chair: Francesco Quaglia (Tor Vergata University of Rome, Italy)

    Synchronization, scheduling, memory management, load balancing, runtime environments, fault tolerance
    Simulation on emerging hardware platforms
    Simulation in cloud environments, simulation as a service
    Data-driven simulation systems: Digital Twins, DDDAS, symbiotic simulation
    Simulation engines and techniques for differentiable simulation and reinforcement learning
    Performance evaluation of simulation systems

2. Modeling Methodology — Track Chair: Adelinde Uhrmacher (University of Rostock, Germany)

    Modeling formalisms and domain-specific languages
    Model reuse, composition, interoperability, and provenance
    Hybrid (continuous & discrete) modeling
    Experiment design, V&V, model calibration, simulation-based inference
    Automatic model generation, data-driven model creation
    Big data-driven modeling and output analysis

3. Applications of advanced discrete simulation methods — Track Co-Chairs: Kevin Jin (University of Arkansas, AS, USA) & Philipp Andelfinger (University of Rostock, Germany)

Case studies considering the application of new or advanced computational methods to applications of contemporary interest, such as:

Domain Applications

    Healthcare and epidemic modeling
    Transportation and urban planning
    Manufacturing and logistics optimization
    Financial systems and market simulations
    Environmental and climate change modeling
    Defense and emergency response scenarios
    Social network and behavior modeling
    Smart city and infrastructure planning
    Gaming and entertainment industry applications

Network and System Simulations

    Wireless, mobile, ad-hoc, sensor network simulations
    Simulation of HPC interconnects, LAN, WAN, and peer-to-peer overlay networks
    Hardware performance prediction via simulation
    Cyber-physical systems
    Cyber security and simulation

Cross-cutting Simulation Applications

    Virtual and augmented reality simulations
    Simulation with Big Data
    Sustainable and energy-efficient simulation

Special Tracks on Emerging Topics:

1. AI and Simulation — Track Chair: Christopher Carothers (Rensselaer Polytechnic Institute, NY, USA)

    Bridging machine learning models with simulation frameworks
    Real-time AI-driven adaptive simulation environments
    Training agents in simulated environments
    Transfer learning from simulation to real-world scenarios
    Using AI to predict future simulation states or events
    Enhancing simulation accuracy through AI-driven predictions
    Incorporating big data analytics into simulation processes
    Using AI to streamline data preprocessing for simulations
    Using AI to validate simulation models and outputs
    Benchmarking AI-driven simulations against traditional methods
    Employing AI algorithms for simulation optimization tasks
    Dynamic reconfiguration of simulations based on AI insights
    Using simulations for data augmentation in deep learning
    Evaluating and testing neural network robustness in simulated scenarios
    Real-world applications of integrating AI and simulation

2. Quantum Computing and Simulation — Track Chair: Prasanna Date (Oak Ridge National Laboratory, TN, USA)

Novel, impactful, and original contributions highlighting quantum simulations including, but not limited to, the following areas are highly encouraged:

    Astronomy
    Biology
    Chemistry
    Chemical Engineering
    Computer Engineering
    Economics
    Electrical & Electronics Engineering
    Environmental Science
    Finance
    Geospatial Science
    High Energy Physics
    Information Science
    Materials Science
    Mechanical Engineering
    Medical Science
    Pharmaceutical Science
    Physics
    Quantum Communication & Cryptography
    Quantum Chemistry
    Quantum Physics

The specific topics in the papers can also address novel quantum algorithms (including but not limited to quantum monte carlo, variational quantum algorithms, quantum machine learning etc.), theoretical contributions, architectures, applications, data embedding techniques, and any other research contributions that aid in quantum simulations.