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International Conference on Statistical Inference in Machine Learning and AI - (ICSIMLAI-27)

13th - 14th January 2027 , Francistown - Botswana

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Call For Papers

The (ICSIMLAI-27) 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 Statistics, 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:

  • 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

Assessment

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.

Publication

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

Submit Your Research Work Register Now