The Data and Text Analytics Lab Research Group

The Data and Text Analytics Lab (DTALab) is a research group of the Department of Engineering “Enzo Ferrari” at the University of Modena and Reggio Emilia, Italy.

DTALab develops trustworthy data-centric AI systems that connect models, data, evidence and explanations. Our research focuses on methods, tools and evaluation frameworks for building AI systems that are accurate, inspectable, robust and reproducible.

The group works at the intersection of data management, natural language processing, large language models, machine learning and explainable AI, with applications in data integration, entity matching, fact-checking, table understanding, time-series analytics, fairness, financial AI and decision support.

Research focus

Evidence-grounded NLP and LLMs

We study NLP and LLM-based systems for fact-checking, source attribution, table question answering, retrieval-augmented generation and decision support over textual, tabular and structured evidence.

Explainable data integration and analytics

We develop methods for data integration, entity matching, time-series analytics and interpretable data pipelines, with a focus on explanations that can be inspected and validated by domain experts.

Robust, fair and auditable AI

We design methods and tools for testing robustness, auditing model behaviour, mitigating fairness harms and understanding how AI systems behave under realistic and adversarial conditions.

Reproducible benchmarks and decision support

We build reproducible evaluation frameworks for textual, tabular, financial and time-series data, connecting model performance to downstream decisions and real-world use cases.

DTALab participates in research, technology transfer and training projects with universities, research centres, public organisations and companies.