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International Conference on Graph Analytics for Networked Engineering Systems

8 - 9 May 2027 Budapest, Hungary Standard / Physical Participation
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$125
virtual · $155 in person
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Registration summary

ConferenceICGANES
ModeStandard / Physical
ParticipationListener
Registration fee$155.00
Bank charges (5.8%)$8.99
Total payable$163.99
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• Conference Session Tracks •
SDGs
SDG-Aligned Research Themes

ICGANES conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.

SDG 4 - Quality Education SDG 9 - Industry, Innovation and Infrastructure SDG 11 - Sustainable Cities and Communities SDG 12 - Responsible Consumption and Production
01 Advancements in Graph Analytics for Predictive Modeling +
This track focuses on the latest methodologies in predictive modeling using graph analytics. Researchers are encouraged to present their findings on the effectiveness of these techniques in various engineering applications.
02 Supervised and Unsupervised Learning in Networked Systems +
This session explores the applications of supervised and unsupervised learning techniques in analyzing networked engineering systems. Contributions should highlight innovative approaches and their implications for system performance.
03 Deep Learning Techniques for Graph-Based Data +
This track examines the integration of deep learning methods with graph-based data structures. Papers should discuss novel architectures and their impact on data interpretation in engineering contexts.
04 Anomaly Detection in Networked Engineering Systems +
This session addresses the challenges and solutions related to anomaly detection within networked systems. Contributions should focus on methodologies that enhance the reliability and security of engineering applications.
05 Network Analysis and Its Applications in Engineering +
This track invites discussions on network analysis techniques and their practical applications in engineering. Researchers are encouraged to share insights on how these methods can optimize system performance.
06 Feature Extraction Techniques for Graph Data +
This session explores innovative feature extraction methods tailored for graph data in engineering systems. Papers should highlight the significance of these techniques in improving model accuracy and efficiency.
07 Social Network Analysis in Engineering Contexts +
This track delves into the applications of social network analysis within engineering disciplines. Contributions should focus on how social dynamics influence engineering outcomes and decision-making processes.
08 Sensor Networks and Industrial IoT: Challenges and Solutions +
This session addresses the complexities associated with sensor networks and the Industrial Internet of Things. Researchers are invited to present innovative solutions that enhance connectivity and data utilization.
09 Model Evaluation and Optimization in Graph Analytics +
This track focuses on the methodologies for model evaluation and optimization in graph analytics. Contributions should discuss best practices and frameworks that ensure robust model performance in engineering applications.
10 Graph Neural Networks: Innovations and Applications +
This session explores the latest advancements in graph neural networks and their applications in engineering. Papers should highlight novel approaches and their potential to transform data analysis in networked systems.
11 Data Visualization Techniques for Networked Data +
This track examines the role of data visualization in interpreting complex networked data. Researchers are encouraged to present innovative visualization techniques that enhance understanding and decision-making in engineering systems.