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Call for Paper

The ICAMMLAI emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Mathematics are explored to promote cross-domain knowledge exchange and collaborative innovation.

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

01
Mathematics in machine learning applications
02
Statistical methods for AI development
03
Algorithms for machine learning optimization
04
Mathematical foundations of AI techniques
05
Data analysis using applied mathematics
06
Modeling uncertainty in machine learning
07
Mathematical modeling of neural networks
08
Applications of linear algebra in AI
09
Machine learning algorithms in practice
10
Mathematical techniques for big data
11
Optimization methods in machine learning
12
Mathematical modeling in robotics
13
Applications of calculus in AI
14
Mathematical approaches to deep learning
15
Statistical learning theory applications
16
Mathematics for natural language processing
17
Recent trends in AI and mathematics
18
Interdisciplinary approaches to AI development
19
Mathematical models for predictive analytics
20
Challenges in mathematics for AI

All submissions will undergo peer review to ensure quality and interdisciplinary relevance.

Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

👉 Register Now

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.

👉 Submit Your Research Work

Event Highlights

  • Keynote sessions by experienced speakers
  • Technical paper presentations across multiple topics
  • Opportunities for academic and professional networking
  • Discussions on current research developments

Contact Us

    Have questions about submission, registration, or publication? We’re happy to help.

  • Email: [email protected]
  • Phone:+91 9940952512

We look forward to your participation and contribution to the ASPHER Conference.