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Call for Paper

The ICAML-SA 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 Computational Science, Data Science 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
Applied machine learning in scientific fields
02
Case studies of ML in scientific research
03
Real-world applications of machine learning
04
Machine learning for experimental data analysis
05
AI techniques for scientific modeling
06
Data-driven decision-making in science
07
Machine learning for predictive maintenance
08
Applications of ML in environmental science
09
Machine learning in social science research
10
AI for optimizing scientific workflows
11
Challenges in applying ML to science
12
Ethics of machine learning applications
13
Machine learning for data-driven discoveries
14
AI in computational biology applications
15
Interdisciplinary approaches to applied ML
16
Machine learning for sensor data analysis
17
AI for enhancing research reproducibility
18
Future trends in applied machine learning
19
Collaborative research using machine learning
20
Machine learning for scientific visualization

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.