[hpc-announce] Call for Papers - IEEE Metacom 2025 Workshop on Large Language Models-Aided Metaverse Based Digital Twin for Smart Society

[Mostafa Fouda]

*** Please accept our apologies if you receive multiple copies of this CFP ***
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CALL FOR PAPERS
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IEEE Metacom 2025 - Workshop
Large Language Models-Aided Metaverse Based Digital Twin for Smart Society
27-29  August 2025, Seoul, Republic of Korea

https://urldefense.us/v3/__https://ieee-metacom.org/index.html__;!!G_uCfscf7eWS!fX4fC2lTnKmyxvpeLpD_W02qC360egA7MG1URNkSrRmxH31v7OGi_-dsIzaTrMpfH7m7uKw78c_7pMMGTEf9nNQEJDfV$ 
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Important Dates
Paper Submission: 13 June 2025
Notification: 30 June 2025
Camera Ready: 15 July 2025
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Submission link: https://urldefense.us/v3/__https://easychair.org/my/conference?conf=metacom2025__;!!G_uCfscf7eWS!fX4fC2lTnKmyxvpeLpD_W02qC360egA7MG1URNkSrRmxH31v7OGi_-dsIzaTrMpfH7m7uKw78c_7pMMGTEf9nL08Hdol$  
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SCOPE AND MOTIVATION

The transformative potential of large language models (LLMs)-aided digital twins is pivotal in creating innovative societies and advanced metaverse environments. Real-time data synchronization and predictive analytics significantly enhance efficiency and decision-making across diverse industries. This technology can revolutionize urban infrastructure, healthcare services, and energy management, fostering more sustainable and optimized living conditions. Additionally, it ensures interoperability and scalability within the metaverse, driving innovation and seamless integration of virtual and physical worlds. The workshop on the future of LLMs-aided digital twins in the metaverse aims to provide valuable insights and foster discussions on developing smart societies. Topics of interest will include integrating natural language processing (NLP) modules in digital twins, using LLMs for scenario simulation and predictive analytics, and case studies showcasing the implementation of LLMs in various industries. Techniques for real-time data synchronization between physical assets and their digital counterparts will also be explored. The workshop will explore developing virtual environments that accurately represent physical spaces, address challenges and solutions for ensuring interoperability and scalability within the metaverse, and leverage digital twins for smart city infrastructure management, traffic optimization, and resource allocation. Furthermore, it will use digital twins to simulate patient outcomes, optimize treatment plans, improve healthcare services, enhance public transportation systems, reduce traffic congestion, and improve logistics. Additionally, it will discuss optimizing energy consumption and integrating renewable energy sources into smart grids, ensuring the protection of sensitive data, addressing biases, fairness, and transparency in LLMs and digital twins, and adhering to legal and regulatory requirements for the use of AI and digital twin technologies.

TOPICS OF INTEREST

The workshop seeks original contributions in the following topical areas, plus others that are not explicitly listed but are closely related:

Integration of natural language processing (NLP) modules in digital twins.
Use of LLMs for scenario simulation and predictive analytics
Case studies showcasing the implementation of LLMs in digital twins for various industries.
Techniques for real-time data synchronization between physical assets and their digital counterparts.
Development of virtual environments that accurately represent physical spaces.
Challenges and solutions for ensuring interoperability and scalability within the metaverse.
Leveraging digital twins for smart city infrastructure management, traffic optimization, and resource allocation
Using digital twins to simulate patient outcomes, optimize treatment plans, and improve healthcare services
Enhancing public transportation systems, reducing traffic congestion, and improving logistics through digital twins
Optimizing energy consumption and integrating renewable energy sources into smart grids using digital twins
Ensuring the protection of sensitive data within digital twin environments.
Addressing biases, fairness, and transparency in LLMs and digital twins.
Adhering to legal and regulatory requirements for using AI and digital twin technologies.


Organizing Committee

Sherief Hashima (RIKEN-AIP, Japan)
Mostafa M. Fouda (Idaho State University, ID, USA)
Akira Uchiyama (Osaka University, Japan)
Zubair Md Fadllulah (Western University, ON, Canada)
Hamada Rizk (Osaka University, Japan)

Best regards,
Mostafa Fouda
Associate Professor
Department of Electrical and Computer Engineering, Idaho State University, ID, USA
Joint Appointee with Idaho National Laboratory (INL)
IEEE Senior Member
Editor of IEEE Internet of Things Journal (Impact Factor: 8.2)
Editor of IEEE Transactions on Vehicular Technology (Impact Factor: 6.1)
Outstanding Associate Editor of IEEE Access (Impact Factor: 3.4)
https://urldefense.us/v3/__http://www.mostafafouda.com__;!!G_uCfscf7eWS!fX4fC2lTnKmyxvpeLpD_W02qC360egA7MG1URNkSrRmxH31v7OGi_-dsIzaTrMpfH7m7uKw78c_7pMMGTEf9nBUVwLwB$  | mfouda at isu.edu