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Journal Publication | Bias in Machine Learning: A Literature Review. Mavrogiorgos, K., Kiourtis, A., Mavrogiorgou, A., Menychtas, A., & Kyriazis, D. (2024). Bias in Machine Learning: A Literature Review. Applied Sciences, 14(19), 8860. https://doi.org/10.3390/app14198860s
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Magazine, Article | XR5.0: Human-Centric AI-Enabled Extended Reality Applications for the Industry 5.0 Era", ERCIM News 137 (May 2024), Special theme: Extended Reality.
Soldatos, J., Makridis, G., & Liarokapis, F. (2024, April 3). XR5.0: Human-centric AI-enabled extended reality applications for the Industry 5.0 era. ERCIM News, 137. https://ercim-news.ercim.eu/en137/special/xr5-0-human-centric-ai-enabled-extended-reality-applications-for-the-industry-5-0-era
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Conference Paper | Impact of Collaborative Robots on Human Trust, Anxiety, and Workload: Experiment Findings. Montini, E., Ploner, G., Matteri, D., Cutrona, V., Rocco, P., Bettoni, A., & Pedrazzoli, P. (2024, September). Impact of collaborative robots on human trust, anxiety, and workload: experiment findings. In IFIP International Conference on Advances in Production Management Systems (pp. 401-415). Cham: Springer Nature Switzerland.
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Conference Paper | UI/UX Sustainable Design: Best Practices for Applications CO2 Emissions Reduction. Kiourtis, A., Mavrogiorgou, A., Zafeiropoulos, N., Mavrogiorgos, K., Karabetian, A., & Kyriazis, D. (2024, June). UI/UX sustainable design: best practices for applications co2 emissions reduction. In 2024 9th International Conference on Smart and Sustainable Technologies (SpliTech) (pp. 01-06). IEEE.
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Conference Paper | XR5.0: Human-Centric AI-Enabled Extended Reality Applications for Industry 5.0. Kiourtis, A., Mavrogiorgou, A., Makridis, G., Kyriazis, D., Soldatos, J., Fatouros, G. (2024, October). Xr5. 0: Human-centric ai-enabled extended reality applications for industry 5.0. In 2024 36th Conference of Open Innovations Association (FRUCT) (pp. 314-323). IEEE.
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Conference Paper | Improving Collaborative Robotics: Insights On The Impact of Human Intention Prediction. Dell’Oca, S., Matteri, D., Montini, E., Cutrona, V., Barut, Z. M., & Bettoni, A. (2024, September). Improving collaborative robotics: Insights on the impact of human intention prediction. In International Workshop on Human-Friendly
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Conference Paper | Motion Trajectory Prediction in Dynamic Human- Robot Shared Workspaces. Samuele, D., Cutrona, V., Montini, E., Matteri, D., Masiero, S., & Bettoni, A. (2025, May). Motion Trajectory Prediction in Dynamic Human-Robot Shared Workspaces. https://doi.org/10.5281/zenodo.15720093.
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Conference Paper | A Protocol for Human-Centric Adaptive User Interfaces: From Static Interaction to Behaviour-Driven Adaptation. Matteri, D., Masiero, S., Dell'Oca, S., Montini, E., Cutrona, V., & Canetta, L. (2025, June). A Protocol for Human-Centric Adaptive User Interfaces: From Static Interaction to Behaviour-Driven Adaptation. In 2025 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC) (pp. 1-10). IEEE. DOI:10.1109/ICE/ITMC65658.2025.11106653
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Conference Paper | A Scalable Data-Driven Methodology for Human Intention Prediction in Diverse Collaborative Scenarios. Dell’Oca, S., Montini, E., Cutrona, V., Matteri, D., Landolfi, G., & Bettoni, A. (2025, June 23). A scalable data‑driven methodology for human intention prediction in diverse collaborative scenarios [Conference paper]. Zenodo. https://doi.org/10.5281/zenodo.15720280
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Conference Paper | Bridging Industrial Expertise and XR with LLM-Powered Conversational Agent. Tomkou, D., Fatouros, G., Andreou, A., Makridis, G., Liarokapis, F., Dardanis, D., ... & Kyriazis, D. (2025). Bridging industrial expertise and xr with llm-powered conversational agents. arXiv preprint arXiv:2504.05527.
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Conference Paper | Integrating Asset Administration Shell with an IIoT Platform for Human-centric Digital Twins Almeida, B., Guedes, J., Ferreira, P., Di Orio, G., Matteri, D., Montini, E., ... & Maló, P. (2025, June). Integrating Asset Administration Shell with an IIoT Platform for Human-Centric Digital Twins. In 2025 21st International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) (pp. 01-08). IEEE. https://doi.org/10.5281/zenodo.16283191
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Conference Paper | Strengthening Effectiveness and Safety of Product Assembly and Repair Processes using Extended Reality Applications in Industry 5.0 domain Mavrogiorgis, E., Tsanakas, S., Zafeiropoulos, N., & Papadakis, N. (2025). Strengthening Effectiveness and Safety of Product Assembly and Repair Processes using Extended Reality Applications in Industry 5.0 domain. https://doi.org/10.5281/zenodo.16284631
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Conference Paper | XR Training in Industry 5.0: Advancing Human-Machine Collaboration with the XR5.0 Training Platform Oliveira, J., Saraiva, T., Shah, H. M., Mavrogiorgis, E., Mavrogiorgou, A., & Kiourtis, A. (2025, June). XR Training in Industry 5.0: Advancing Human-Machine Collaboration with the XR5. 0 Training Platform. In International Conference on Extended Reality (pp. 93-100). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-97769-5_7
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Conference Paper | Human-Centric AI-Enabled Extended Reality Reference Architecture for Industry 5.0 N. Tousert et al., "Human-Centric AI-Enabled Extended Reality Reference Architecture for Industry 5.0," 2025 11th International Conference on Control, Decision and Information Technologies (CoDIT), Split, Croatia, 2025, pp. 966-971, doi: 10.1109/CoDIT66093.2025.11321635.
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Journal Paper | Human-Centric AI-Enabled Extended Reality Reference Architecture for Industry 5.0 E. V. Votyakov, A. Andreou and F. Liarokapis, "An Augmented Reality System with an Offline LSTM-Based Fault Recognition Model for Sewer Pipeline Inspection," in IEEE Access, doi: 10.1109/ACCESS.2026.3657618. keywords: {Pipelines;Inspection;Long short term memory;Feature extraction;Maintenance;Accuracy;Machine learning;Computational modeling;Videos;Fault diagnosis;Augmented reality;sewer pipeline faults;machine learning;handcrafted features;LSTM},
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Journal Paper | Human-Centric Integration of AI and Extended Reality in Industry 5.0: A Multilevel Framework and Minimum Viable Model Rosinha, António and Reis, Joaquim and Oliveira, Toacy and Horozal, Feryal and Almeida, Bruno and Maló, Pedro, Human-Centric Integration of AI and Extended Reality in Industry 5.0: A Multilevel Framework and Minimum Viable Model. Available at SSRN: https://ssrn.com/abstract=6151192 or http://dx.doi.org/10.2139/ssrn.6151192
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Conference Paper | The Embodiment Trap: When AI Has a Body in Education Constantinides, M., Ppali, S., Charalambidou, C., & Liarokapis, F. (2026). The Embodiment Trap: When AI Has a Body in Education. In Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26). ACM. https://doi.org/10.5281/zenodo.19205747
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