International Conference on Data-Driven Risk Assessment in Engineering

ICDDRAE

5th Dec – 6th Dec 2026 Athens, Greece

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Registration Summary

Conference ICDDRAE

Date 5th Dec – 6th Dec 2026

Location Athens, Greece

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Data-Driven Risk Assessment Methodologies +

This track focuses on innovative methodologies for data-driven risk assessment in engineering contexts. It aims to explore various frameworks and approaches that enhance the accuracy and reliability of risk evaluations.

SDG 9 SDG 11

02 Predictive Modeling Techniques in Engineering +

This session will delve into the latest predictive modeling techniques applicable to engineering challenges. Researchers are encouraged to present their findings on model development, validation, and application in real-world scenarios.

SDG 9

03 Supervised and Unsupervised Learning Applications +

This track will examine the applications of both supervised and unsupervised learning in engineering data analysis. Contributions should highlight novel algorithms and their effectiveness in addressing engineering problems.

SDG 9 SDG 11

04 Deep Learning for Anomaly Detection +

This session is dedicated to the exploration of deep learning techniques for anomaly detection in engineering systems. Papers should discuss innovative architectures and their performance in identifying faults and irregularities.

SDG 9

05 Feature Extraction and Selection Strategies +

This track will cover advanced strategies for feature extraction and selection in data-driven engineering applications. Participants are invited to share methodologies that improve model performance and interpretability.

SDG 9

06 Risk Quantification and Management +

This session will focus on methodologies for risk quantification and management in engineering projects. Contributions should address both theoretical frameworks and practical applications in various engineering domains.

SDG 9 SDG 11

07 Predictive Maintenance and Fault Prediction +

This track aims to explore predictive maintenance strategies and fault prediction techniques in industrial settings. Papers should present case studies or novel approaches that enhance equipment reliability and operational efficiency.

SDG 9 SDG 12

08 Industrial IoT and System Monitoring +

This session will investigate the role of Industrial IoT in enhancing system monitoring and risk assessment. Contributions should focus on data integration, real-time analytics, and decision-making processes.

SDG 9 SDG 11

09 Model Evaluation and Performance Metrics +

This track will address the critical aspects of model evaluation and performance metrics in engineering applications. Participants are encouraged to discuss novel evaluation techniques and their implications for model reliability.

SDG 9

10 Simulation and Analytics in Engineering +

This session will explore the intersection of simulation techniques and data analytics in engineering. Papers should highlight how these tools can be leveraged to improve risk assessment and decision-making.

SDG 9 SDG 11

11 Adaptive Learning in Engineering Systems +

This track will focus on adaptive learning approaches that enhance the adaptability and resilience of engineering systems. Contributions should explore the integration of adaptive algorithms in real-time decision-making frameworks.

SDG 9 SDG 11