International Conference on Machine Learning and Data Mining in Engineering

ICMLDME

11th Sep – 12th Sep 2026 Manila, Philippines

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Registration Summary

Conference ICMLDME

Date 11th Sep – 12th Sep 2026

Location Manila, Philippines

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

Calculated based on 5.8% of the registration fee

Discount USD 0.00

Total Payable 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 Advancements in Predictive Modeling Techniques +

This track focuses on the latest methodologies in predictive modeling within engineering contexts. It aims to explore novel algorithms and frameworks that enhance the accuracy and efficiency of predictions in various engineering applications.

SDG 9 SDG 12

02 AI-Driven Process Optimization in Engineering +

This session will delve into the integration of artificial intelligence in optimizing engineering processes. Participants will discuss case studies and innovative approaches that demonstrate significant improvements in efficiency and resource management.

SDG 9 SDG 12

03 Anomaly Detection in Engineering Systems +

This track addresses the challenges and solutions related to anomaly detection in engineering systems. It will highlight techniques that leverage data mining to identify and mitigate anomalies, ensuring system reliability and performance.

SDG 9 SDG 11

04 Sensor Analytics for Smart Engineering Solutions +

This session emphasizes the role of sensor analytics in enhancing engineering practices. Discussions will include data collection, processing, and interpretation techniques that lead to smarter engineering solutions and decision-making.

SDG 9 SDG 11

05 Simulation Data and Its Impact on Engineering Design +

This track explores the utilization of simulation data in the engineering design process. It will cover methodologies for analyzing simulation outputs and their implications for improving design accuracy and innovation.

SDG 9 SDG 12

06 Intelligent Systems for Engineering Applications +

This session focuses on the development and implementation of intelligent systems tailored for engineering applications. Participants will share insights on how these systems enhance operational efficiency and decision-making capabilities.

SDG 9 SDG 12

07 Data Mining Techniques for Engineering Insights +

This track aims to showcase various data mining techniques that extract valuable insights from engineering data. Emphasis will be placed on methodologies that facilitate data-driven decision-making in engineering projects.

SDG 9 SDG 12

08 Machine Learning Applications in Structural Engineering +

This session will explore the application of machine learning techniques in the field of structural engineering. Participants will discuss how these methods can improve structural analysis, design, and maintenance.

SDG 9 SDG 12

09 Big Data Analytics in Engineering +

This track addresses the challenges and opportunities presented by big data in engineering. It will focus on analytics techniques that can handle large datasets to drive innovation and efficiency in engineering practices.

SDG 9 SDG 12

10 Real-Time Data Processing for Engineering Applications +

This session will investigate the importance of real-time data processing in engineering applications. Discussions will center around technologies and methodologies that enable timely data analysis for immediate decision-making.

SDG 9 SDG 12

11 Ethical Considerations in AI and Data Mining in Engineering +

This track will explore the ethical implications of using AI and data mining in engineering. It aims to foster discussions on responsible practices and the societal impact of these technologies in engineering fields.

SDG 16 SDG 17