International Conference on Statistical Learning and Machine Learning Integration - (ICSLMLI-27)


27th - 28th May, 2027 | Barcelona, Spain

Multi-format (In-person/Virtual)

Registration Options

Explore conference registration categories designed for every mode of participation.

Important Dates

Pre-registration Deadline

27th April, 2027

Paper Submission Deadline

2nd May, 2027

Last Date Of Registration

12th May, 2027

Date Of Conference

27th - 28th May, 2027

Downloads

Call for Papers

The (ICSLMLI-27) is dedicated to advancing research excellence by bringing together leading scholars, scientists, and professionals from across the globe. It provides a platform for the dissemination of high-quality research and innovative methodologies.

With a strong focus on Statistics, the conference promotes research that contributes to academic depth, practical insights, and interdisciplinary knowledge integration.

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

  • Integration of statistical learning and machine learning
  • Applications of machine learning in statistics
  • Statistical methods for predictive modeling
  • Bayesian statistics and machine learning synergy
  • Statistical learning techniques for big data
  • Feature selection methods in statistical learning
  • Statistical validation of machine learning models
  • Deep learning applications in statistical analysis
  • Statistical approaches to model interpretability
  • Ensemble methods in statistical learning
  • Statistical methods for time series forecasting
  • Applications of neural networks in statistics
  • Statistical learning in bioinformatics
  • Causal inference in machine learning contexts
  • Statistical frameworks for unsupervised learning
  • Statistical software for machine learning applications
  • Challenges in integrating statistics and machine learning
  • Statistical methods for anomaly detection
  • Ethics in statistical machine learning applications
  • Future directions in statistical learning research

Peer Review Process

All submissions will be evaluated through a structured peer-review process to ensure academic rigor and contribution to the field. Accepted papers will be presented and may be considered for publication in high-quality journals and indexed conference proceedings.

Registration Details

Secure your participation by completing the registration process at the earliest. Limited presentation slots are allocated on a first-come, first-served basis.

Publication Opportunities

High-quality submissions will be prioritized for publication opportunities in recognized journals and indexed proceedings.