Hybrid Conferencee

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

26th - 27th September 2026 | Lima, Peru

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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Lima. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Lima event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Lima conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Lima, 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 Lima."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICEADM aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Data Mining, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Applications of data mining in engineering
02
Data mining for process optimization techniques
03
Machine learning in engineering applications
04
Data mining for predictive analytics
05
Data-driven methodologies in engineering
06
Data mining for supply chain optimization
07
Statistical analysis in engineering applications
08
Data mining for project management
09
Integration of AI in engineering data mining
10
Data mining for resource allocation
11
Data mining in manufacturing processes
12
Real-time analytics for engineering applications
13
Data mining for safety improvements
14
Data mining in construction engineering
15
Data mining for product lifecycle management
16
Data mining for customer behavior analysis
17
Collaborative data mining in engineering teams
18
Data mining for performance enhancement
19
Data mining for regulatory compliance
20
Future directions in engineering data mining