Hybrid Conferencee

International Conference on Machine Learning and Data Mining in Engineering (ICMLDME - 26)

17th - 18th June 2026 | Kathmandu, Nepal
Sample Abstract
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Conference Brochure
Sample Full Paper
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Conference Notifications:

"Be sure to check this section regularly for all Research Plus International Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Kathmandu. 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 Kathmandu 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 Kathmandu conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Kathmandu, 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 Kathmandu."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICMLDME 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
Machine learning algorithms for engineering applications
02
Data mining techniques in structural engineering
03
Predictive analytics for engineering design
04
Big data challenges in engineering fields
05
AI applications in engineering problem solving
06
Data-driven optimization in engineering processes
07
Statistical methods for engineering data analysis
08
Machine learning for materials engineering
09
Engineering data visualization techniques
10
Real-time data processing in engineering
11
Data mining for fault detection in engineering
12
Integration of IoT in engineering analytics
13
Sustainability metrics in engineering projects
14
Data mining for risk assessment in engineering
15
Collaborative engineering through data sharing
16
Machine learning for energy systems
17
Data-driven innovation in engineering education
18
Ethics in machine learning applications
19
Future of data mining in engineering
20
Case studies of successful data mining