Call For Papers

The topics of interest for submission include, but are not limited to:

Track 1: Statistical Learning and Modeling
  • Statistical Learning

  • Probabilistic Models

  • Bayesian Learning

  • Regression and Classification

  • Multivariate Modeling

  • Time Series Modeling

  • Nonparametric Learning

  • Uncertainty Quantification

  • Model Selection

  • Computational Statistics

Track 2: Machine Learning with Statistical Foundations
  • Supervised and Unsupervised Learning

  • Deep Learning Methods

  • Reinforcement Learning

  • Feature Representation

  • Model Evaluation and Validation

  • Statistical Optimization

  • Scalable Learning Algorithms

  • Robust Learning Methods

  • Transfer Learning

  • Data-Driven Modeling

Track 3: AI Algorithms and Statistical Intelligence
  • Intelligent Algorithms

  • Probabilistic Reasoning

  • Statistical Decision Methods

  • Knowledge Representation

  • Natural Language Processing

  • Computer Vision

  • Human-AI Interaction

  • Explainable AI

  • Autonomous Systems

  • AI System Design

Track 4: Data Analytics and Applied Statistical AI
  • Data Science Methods

  • Big Data Analytics

  • Predictive Analytics

  • Statistical Data Analysis

  • Data Visualization

  • Risk and Reliability Analysis

  • Optimization and Decision-Making

  • Business Intelligence

  • Social and Behavioral Data

  • Interdisciplinary Applications