AI-driven Data Science

About AI-Driven Data Science

AI-Driven Data Science focuses on helping people extract knowledge, generate insights and support decision making through advanced AI technologies. The challenge addresses both the automation of data science processes and the development of more powerful AI-driven analytical methods.

The research brings together expertise from machine learning, reasoning, data management, computer vision, knowledge representation and responsible AI. Through collaboration across partners and disciplines, FAIR researchers develop methods that make data science more accessible, reliable and impactful.

Research Objectives

More Powerful Data Science

Developing AI systems that help users discover patterns, generate insights and support complex decision making.

More Automated Data Science

Reducing the effort required to build and deploy AI models through automation and AI-assisted workflows.

More Trustworthy AI

Ensuring transparency, explainability and responsible deployment of AI technologies.

Work Packages

WP1 – AI-Driven Data Engineering

Methods for preparing, integrating and managing complex data.

WP2 – Symbolic and Subsymbolic Learning and Reasoning

Combining machine learning with reasoning and structured knowledge.

WP3 – AI-Assisted Data Exploration

Supporting users in exploring and understanding complex datasets.

WP4 – Automation in Machine Learning

Automating model development, optimization and deployment.

WP5 – Understanding Images and Audio

Developing AI technologies capable of interpreting visual and auditory information.

WP6 – Responsible AI and Decision Support Systems

Supporting trustworthy AI and decision making through explainable and reliable technologies.