The ENERGATE project, coordinated by the DSS Laboratory, EPU-NTUA, proudly participated in the EEITE 2025 Conference, a dynamic platform gathering leading experts, researchers, and practitioners in cutting-edge fields such as IoT, AI, wireless networks, cybersecurity, and energy efficiency.

At the conference, two impactful papers were presented by NTUA researchers, showcasing innovative approaches to enhance energy efficiency in buildings:

• ML-Based Decision Support System for Energy Efficiency Retrofits

  Authors: D. Stoian, K. Kefalas, I. Andreoulaki, K. Papapostolou, V. Marinakis
  📄 Read on IEEE Xplore

  This paper focuses on the role of machine learning in guiding energy renovation strategies. The study proposes a decision support system that helps stakeholders identify the most effective retrofit measures based on past project data.

• Assessing Investment Risks in Energy Efficiency Projects Using AHP for Group Decision Making

  Authors: I. Andreoulaki, A. Papapostolou, V. Marinakis
  📄 Read on IEEE Xplore

  This study addresses the challenges of financing energy efficiency projects in buildings, where the high upfront costs often discourage investors despite long-term benefits.

The participation of ENERGATE at EEITE 2025 highlights its commitment to advancing energy efficiency through data-driven, collaborative decision-making tools that support sustainable building renovations.

For more information about EEITE 2025, visit here.

You can download the presentations here:

1. ML-Based Decision Support System for Energy Efficiency Retrofits.
2. Assessing Investment Risks in Energy Efficiency Projects Using AHP For Group Decision Making.