Hybrid Conferencee

International Conference on Data Mining in Civil and Structural Engineering (ICDMCSE - 26)

23rd - 24th October 2026 | Brasilia, Brazil

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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 Brasilia conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Brasilia, 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 Brasilia."
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 3
SDG 3 Good Health and Well-being
SDG 7
SDG 7 Affordable and Clean Energy
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

Innovations in Structural Health Monitoring

This track focuses on the latest advancements in structural health monitoring technologies and methodologies. Participants will explore the integration of data mining techniques to enhance the assessment and maintenance of civil structures.

Track 02

Predictive Modeling in Civil Engineering

This session will delve into the application of predictive modeling techniques in civil engineering projects. Emphasis will be placed on how data mining can improve forecasting and decision-making processes.

Track 03

Data Analytics for Building Performance Optimization

This track examines the role of data analytics in optimizing building performance throughout its lifecycle. Presentations will highlight case studies that demonstrate the impact of data-driven approaches on energy efficiency and occupant comfort.

Track 04

Risk Assessment in Structural Engineering

This session addresses the methodologies for risk assessment in structural engineering, emphasizing the use of data mining to identify and mitigate potential hazards. Participants will discuss frameworks for integrating risk analysis into design and maintenance practices.

Track 05

Sensor Data Analysis for Infrastructure Management

This track focuses on the analysis of sensor data collected from civil infrastructure. Discussions will center around innovative data mining techniques that can extract actionable insights for effective infrastructure management.

Track 06

Simulation Techniques in Civil Engineering

This session explores the use of simulation techniques in civil engineering, particularly in conjunction with data mining methods. Participants will share insights on how simulations can enhance the understanding of complex engineering systems.

Track 07

Maintenance Analytics for Structural Integrity

This track highlights the importance of maintenance analytics in ensuring structural integrity. Presentations will cover methodologies that leverage data mining to optimize maintenance schedules and improve safety outcomes.

Track 08

Big Data Challenges in Civil Engineering

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

Track 09

Machine Learning Applications in Structural Engineering

This track focuses on the application of machine learning algorithms in structural engineering contexts. Participants will explore case studies that demonstrate the effectiveness of these techniques in enhancing predictive capabilities.

Track 10

Data-Driven Decision Making in Civil Projects

This session examines how data-driven decision-making processes can transform civil engineering projects. Emphasis will be placed on the role of data mining in facilitating informed choices throughout project lifecycles.

Track 11

Emerging Trends in Data Mining for Civil Engineering

This track explores emerging trends and future directions in data mining applications within civil engineering. Participants will discuss innovative approaches and technologies that are shaping the future of the field.