Hybrid Conferencee

International Conference on Engineering Applications of Data Mining (ICEADM - 26)

12th - 13th August 2026 | Edinburgh, UK

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Call for Papers Extended:
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Certificate of Presentation:
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Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Edinburgh conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
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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 Edinburgh."
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 8
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
Track 01

Innovative Approaches in Predictive Modeling

This track focuses on advanced methodologies in predictive modeling tailored for engineering applications. Participants will explore case studies and novel algorithms that enhance forecasting accuracy in various engineering domains.

Track 02

Data Mining Techniques for Process Optimization

This session will delve into the application of data mining techniques to optimize engineering processes. Attendees will discuss strategies for improving efficiency and reducing costs through data-driven insights.

Track 03

Anomaly Detection in Engineering Systems

This track addresses the critical role of anomaly detection in maintaining the integrity of engineering systems. Researchers will present innovative methods for identifying irregularities in sensor data and their implications for system reliability.

Track 04

AI Applications in Engineering Analytics

This session highlights the integration of artificial intelligence in engineering analytics. Participants will examine how AI-driven solutions can enhance data interpretation and decision-making processes in engineering contexts.

Track 05

Sensor Data Analysis for Industrial Applications

This track focuses on the analysis of sensor data to drive improvements in industrial applications. Presentations will cover techniques for extracting actionable insights from large volumes of sensor-generated data.

Track 06

Workflow Analytics in Engineering Projects

This session explores the role of workflow analytics in optimizing engineering project management. Discussions will center on methodologies for analyzing workflows to enhance productivity and collaboration.

Track 07

Industrial Analytics: Trends and Innovations

This track will showcase the latest trends and innovations in industrial analytics. Participants will share insights on how data mining is transforming industrial operations and driving competitive advantages.

Track 08

Fault Detection Techniques in Engineering

This session focuses on the development and application of fault detection techniques in various engineering fields. Researchers will present their findings on methods that improve fault identification and system maintenance.

Track 09

Engineering Informatics: Bridging Data and Decision-Making

This track emphasizes the importance of engineering informatics in facilitating data-driven decision-making. Presentations will explore frameworks that connect data analysis with practical engineering solutions.

Track 10

Data Mining for Sustainable Engineering Practices

This session investigates the role of data mining in promoting sustainable engineering practices. Participants will discuss how data-driven approaches can lead to environmentally friendly and resource-efficient engineering solutions.

Track 11

Emerging Trends in Data-Driven Engineering

This track will cover emerging trends in data-driven engineering practices. Researchers will present innovative applications of data mining that are shaping the future of engineering disciplines.