EVENTS

The 2025 edition of the EuADS Summer School is dedicated to Automated Data Science (AutoDS) and will cover important branches of this research field in a tutorial style. With the increasing complexity of data science projects and the limited availability of human expertise, the idea of automating or partially automating the work of a data scientist has come to the fore in recent years. AutoDS aims to streamline the data science workflow, making processes such as data pre-processing, feature engineering, model selection, evaluation and deployment faster and more accessible. By reducing manual intervention, AutoDS enables both non-experts and data scientists to work more efficiently, scale projects, and make data science accessible to a broader audience. It leverages tools from automated machine learning (AutoML) frameworks, automated visualisation and interpretability techniques to enable efficient model tuning, robust evaluation and easy deployment. Despite its advantages in efficiency and scalability, challenges remain in automating subtasks that are context-dependent and require human interaction, as well as model interpretability, dependence on data quality, and ethical concerns related to bias in automated models. These and other issues will be addressed in a series of five tutorials delivered by leading experts in the field.

The Summer School emphasizes the interdisciplinary nature of data science and is primarily aimed at PhD students, postdoctoral and early-career researchers with a basic grounding in data science, statistics, machine learning, AI, or related fields, and an interest in interdisciplinary research and applications.

Institutions

• LMU Munich, Germany
• U of Bristol, UK
• EuADS Germany
• U of Essex, UK
• STATEC, Luxembourg
• U of Göttingen, Germany
• Data 3.0 Ldt., UK
• CUNEF Universidad, Spain
• U of Cordoba, Spain
• NeuralWave Technologies, Luxembourg
• Imperial College London, UK
• Bielefeld University, Germany