Hybrid Conferencee

International Conference on Data Mining for Engineering Process Optimization (ICDMPOE - 26)

16th - 17th November 2026 | Kuwait City, Kuwait

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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:
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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 Kuwait City."
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 8
SDG 8 Decent Work and Economic Growth
SDG 9
SDG 9 Industry, Innovation and Infrastructure
SDG 12
SDG 12 Responsible Consumption and Production
Track 01

Advanced Data Mining Techniques in Engineering

This track focuses on the latest advancements in data mining methodologies applicable to engineering processes. Participants will explore innovative algorithms and their effectiveness in enhancing engineering outcomes.

Track 02

Predictive Modeling for Process Optimization

This session addresses the role of predictive modeling in optimizing engineering processes. Attendees will discuss case studies demonstrating the impact of predictive analytics on operational efficiency.

Track 03

Workflow Analysis and Improvement Strategies

This track emphasizes the importance of workflow analysis in engineering environments. Presentations will highlight techniques for identifying bottlenecks and improving overall process efficiency.

Track 04

Machine Learning Applications in Industrial Analytics

This session delves into the application of machine learning techniques in industrial settings. Participants will examine how these technologies can drive performance improvements and decision-making.

Track 05

Decision Support Systems for Engineering Performance

This track explores the development and implementation of decision support systems tailored for engineering challenges. Discussions will focus on enhancing decision-making processes through data-driven insights.

Track 06

Operational Efficiency through Data-Driven Insights

This session investigates how data mining can lead to significant improvements in operational efficiency within engineering processes. Case studies will illustrate successful implementations and measurable outcomes.

Track 07

Performance Metrics in Process Engineering

This track examines the critical performance metrics used to evaluate engineering processes. Participants will discuss methodologies for measuring and improving these metrics through data mining.

Track 08

Industrial Analytics: Trends and Future Directions

This session provides an overview of current trends in industrial analytics and their implications for engineering processes. Experts will share insights on future directions and emerging technologies in this field.

Track 09

Integrating Data Mining with Engineering Design

This track focuses on the integration of data mining techniques into the engineering design process. Participants will explore how data-driven approaches can enhance design efficiency and innovation.

Track 10

Real-time Data Mining for Process Control

This session highlights the application of real-time data mining techniques in process control environments. Discussions will center on the benefits of immediate data analysis for operational decision-making.

Track 11

Case Studies in Data Mining for Engineering Optimization

This track presents a series of case studies showcasing successful applications of data mining in engineering optimization. Participants will gain insights into practical implementations and the resulting benefits.