Digital Twins for Energy-Efficient Data Centers (DT4DC)
DT4DCwebsite: https://dt4dc.hpc4ai.unito.it/
Aims and Scope
As the digital landscape rapidly expands, data centers have become integral to the infrastructure of modern society, supporting everything from cloud computing to AI-driven applications. However, this growth has come with a significant environmental cost, making energy efficiency a critical concern. To address this challenge, we invite submissions to a special session dedicated to “Digital Twins for Energy-Efficient Data Centers”, focusing on innovative approaches and cutting-edge technologies that enhance sustainability and efficiency.
Topics of interest include (not limited to) the following:
We encourage contributions from a wide range of disciplines, including but not limited to:
- Energy Efficiency and Sustainability: Strategies for reducing energy consumption and carbon footprints in data centers through digital twin technology.
- Predictive Maintenance: Utilizing digital twins for real-time monitoring and maintenance of data center infrastructure, minimizing downtime and operational costs.
- AI and Machine Learning Integration: Leveraging AI and ML to enhance the functionality and efficiency of digital twins in data center environments.
- IoT and Sensor Networks: Implementing IoT devices and sensor networks for detailed data acquisition and monitoring, enabling more precise control over energy use.
- Disruptive Technologies: New, groundbreaking technologies and methodologies that push the boundaries of what is possible with digital twins in data centers.
- Interdisciplinary Approaches: Collaborative efforts that bring together experts from various fields to tackle the complex challenges of energy efficiency in data centers.
Important dates
Paper abstracts: November 30, 2025, 23:59 AOE
Full paper submission: December 20, 2025, 23:59 AOE
Author notification: January 7, 2026
Camera ready full papers: January 20, 2026
Submission guidelines
Authors are invited to submit original research papers, case studies, or review articles that align with the session’s theme. Submissions should highlight the potential for practical implementation, scalability, and the interdisciplinary nature of the work.
Authors should submit a full paper not exceeding 8 pages in the IEEE Conference Proceedings Format (double-column, 10pt size fonts) and follow format guidelines found at https://www.ieee.org/conferences/publishing/templates.html.
For submission, please refer to the Easychair submission system as indicated in the Main Conference webpage, and make sure that you select the “Digital Twins for Energy-Efficient Data Centers” track.
Double-bind review: the first page of the paper should contain only the title and abstract; in the reference list, references to the authors own work should appear as “omitted for blind review” entries.
Chairs
Lavinia Chiara Tagliabue, University of Turin (contact: laviniachiara.tagliabue@unito.it)
Robert Birke, University of Turin
Stefano Rinaldi, University of Brescia
Silvia Meschini, University of Turin
Program Committee
Marco Beccali, Department of Engineering, University of Palermo, Italy
Ibrahim Yitmen, Department of Construction Engineering and Lighting Science , School of Engineering, Jonkoping University, Sweden
Habib Sadri, Department of Construction Engineering and Lighting Science, School of Engineering, Jonkoping University, Sweden
Jochen Teizer, Department of Civil Mechanical Engineering Digital Building Technologies, Technical University of Denmark, Denmark
Emanuela Quaquero, Department of Civil Environmental and Architectural Engineering, University of Cagliari, Italy
Luigi Piegari, Department of Electronic, Information and Bioengineering, Politecnico di Milano, Italy
Rossano Scoccia, Department of Energy, Politecnico di Milano, Italy
Pablo Vicente-Legazpi, BDTA – Building Digital Twin Association, Barcelona, Spain
Eduard Losco, BDTA – Building Digital Twin Association, Barcelona, Spain
Massimiliano Manfren, Department of Civil and Environmental Engineering, University of Southampton, United Kingdom of Great Britain and Northern Ireland
Emanuela Oberti, Computer Science Department, University of Turin, Italy
Paola Gasbarri, Computer Science Department, University of Turin, Italy
Dr. Parameshachari B D, Nitte Meenakshi Institute of Technology, Bengaluru, Karnataka, India
Marta Boscariol, Department of Management, University of Turin, Italy