Computational Statistics and Data Science

Tasks, Goals and Contents:

The committee is dedicated to all aspects of computational statistics and data science, wherein it enables the identification of patterns within extensive datasets and facilitates data-driven decision-making across diverse application domains. The broad spectrum of the committee thus encompasses using computer-aided techniques and algorithms to perform statistical analyses. Statistical methods are combined with computer science techniques to tackle complex problems in data analysis, especially when it comes to large data sets or computationally intensive calculations. The aim of the committee is to advance innovative research in the field of computational statistics and data science and to promote the application of advanced statistical methods in various areas.

Topic Selection:

• Statistical modelling and methodology, esp. for massive and complex data
• Machine learning and artificial intelligence (e.g., artificial neural networks, large language models, multimodal AI)
• Big data analytics
• Data mining
• Causal inference
• Data processing and analysis
• Data management and integration
• Data visualisation
• Programming and statistical software (e.g. Python, R, Julia)
• Explainability and ethical aspects in data analytics
• Practical applications in various research areas