Hybrid Conferencee

International Conference on Digital Twins and Machine Learning (ICDTML - 26)

14th - 15th November 2026 | Los Angeles, USA

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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 Los Angeles. 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 Los Angeles 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 Los Angeles conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Los Angeles, 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 Los Angeles."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICDTML 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 Machine Learning, 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
Digital twins in predictive maintenance
02
Machine learning for virtual modeling
03
Applications of digital twins in engineering
04
Data integration for digital twin systems
05
Real-time simulations using digital twins
06
Challenges in creating digital twins
07
Impact of digital twins on industry 4.0
08
AI-driven insights from digital twins
09
Case studies of digital twin implementations
10
Interoperability of digital twin technologies
11
Digital twins for asset management
12
Machine learning algorithms for digital twins
13
Future trends in digital twin technology
14
Digital twins in smart cities
15
Ethical considerations in digital twin usage
16
Scalability of digital twin solutions
17
Digital twins for environmental monitoring
18
User experience in digital twin applications
19
Data security in digital twin systems
20
Machine learning for enhanced digital twins