Hybrid Conferencee

International Conference on Data Mining for Structural Integrity and Engineering Health (ICDMSIEH - 26)

23rd - 24th October 2026 | San Juan, Puerto Rico

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Call for Papers Extended:
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Certificate of Presentation:
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Abstract Submissions Open:
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Networking with Global Experts:
"Engage with researchers and professionals from around the world at the San Juan conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in San Juan, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in San Juan."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Conference Session Tracks

SDG Wheel

Aligned with

UN Sustainable Development Goals

This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals. It fosters knowledge exchange, innovation, and collaborative engagement.

SDG 7
SDG 7 Affordable and Clean Energy
SDG 9
SDG 9 Industry, Innovation and Infrastructure
SDG 11
SDG 11 Sustainable Cities and Communities
Track 01

Advancements in Predictive Maintenance Techniques

This track focuses on the latest methodologies in predictive maintenance, emphasizing data-driven approaches to enhance the longevity of structural assets. Participants will explore case studies demonstrating the effectiveness of these techniques in various engineering contexts.

Track 02

Data Mining Applications in Structural Health Monitoring

This session will delve into innovative data mining applications that facilitate real-time structural health monitoring. Researchers will present findings on how sensor analytics can significantly improve the assessment of infrastructure integrity.

Track 03

Risk Assessment Models for Civil Infrastructure

This track aims to discuss the development and implementation of risk assessment models tailored for civil infrastructure. Emphasis will be placed on integrating data mining techniques to predict potential failures and enhance decision-making processes.

Track 04

Sensor Analytics for Building Performance Optimization

This session will explore the role of sensor analytics in optimizing building performance through data mining techniques. Participants will examine how data-driven insights can lead to improved energy efficiency and occupant comfort.

Track 05

Failure Prediction in Engineering Systems

This track will cover methodologies for failure prediction in various engineering systems using advanced data mining techniques. Attendees will learn about the integration of historical data and machine learning models to foresee potential structural failures.

Track 06

Innovative Data Mining Techniques for Structural Integrity

This session will highlight cutting-edge data mining techniques specifically designed for assessing structural integrity. Researchers will share their findings on the application of these techniques in real-world engineering scenarios.

Track 07

Machine Learning Approaches in Engineering Health Analytics

This track will focus on the application of machine learning algorithms in engineering health analytics. Participants will discuss how these approaches can enhance the understanding of structural behaviors and maintenance needs.

Track 08

Big Data Challenges in Structural Engineering

This session will address the challenges posed by big data in the field of structural engineering. Experts will discuss strategies for effectively managing and analyzing large datasets to derive meaningful insights.

Track 09

Integrating IoT and Data Mining for Infrastructure Monitoring

This track will explore the integration of Internet of Things (IoT) technologies with data mining techniques for enhanced infrastructure monitoring. Discussions will focus on the implications of real-time data collection and analysis for structural health.

Track 10

Data-Driven Decision Making in Civil Engineering

This session will examine the role of data-driven decision-making processes in civil engineering practices. Participants will learn how data mining can inform strategic planning and risk management in infrastructure projects.

Track 11

Case Studies in Data Mining for Structural Engineering

This track will present a series of case studies showcasing successful applications of data mining in structural engineering. Attendees will gain insights into practical implementations and the resulting benefits for structural integrity and safety.