Call for Paper
The ICSIMLAI 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,Data Science 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:
- Statistical inference in machine learning
- Bayesian statistics for AI applications
- Statistical challenges in deep learning
- Causal inference in machine learning models
- Statistical methods for model evaluation
- Feature selection techniques in AI
- Statistical learning theory and applications
- Data preprocessing for machine learning
- Statistical frameworks for AI ethics
- Statistical tools for big data analytics
- Statistical methods for reinforcement learning
- Interpretability of machine learning models
- Statistical issues in data privacy
- Statistical modeling of complex systems
- Statistical techniques for time series analysis
- Unsupervised learning and statistical methods
- Statistical evaluation of AI systems
- Transfer learning in statistical contexts
- Statistical power analysis in AI studies
- Statistical education for machine learning
Peer Review & Quality
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
Secure your participation by completing the registration process at the earliest. Limited presentation slots are allocated on a first-come, first-served basis.
Publication
High-quality submissions will be prioritized for publication opportunities in recognized journals and indexed proceedings.