• Home
  • Call for Paper

Call for Paper

The ICMLDSI 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 Artificial Intelligence,Data Science,Machine Learning 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
Integrating machine learning with data science
02
Data preprocessing techniques for machine learning
03
Machine learning in big data environments
04
Collaborative filtering in data science
05
Machine learning for time series analysis
06
Data science methodologies for machine learning
07
Challenges in machine learning integration
08
Machine learning for anomaly detection
09
Data-driven insights from machine learning
10
Machine learning in IoT applications
11
Ethical implications of data science integration
12
Machine learning frameworks and libraries
13
Real-time data processing with machine learning
14
Machine learning for predictive maintenance
15
Data science tools for machine learning
16
Interdisciplinary approaches to data science
17
Machine learning for customer behavior analysis
18
Impact of AI on data science methodologies
19
Machine learning in education and training
20
Future of machine learning and data science

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.