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Siandoย  updated a dataset 13 days ago
DAISLab-Unisa/AIME-Dataset
Siandoย  published a dataset 13 days ago
DAISLab-Unisa/AIME-Dataset
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Organization Card

๐Ÿงช DAISLab โ€” University of Salerno

Data, Artificial Intelligence & Systems Lab
Department of Computer Science ยท University of Salerno, Italy


About Us

DAISLab is a research laboratory at the University of Salerno (UNISA), Italy, operating within the Department of Computer Science. Our work sits at the intersection of Natural Language Processing, Information Retrieval, Retrieval-Augmented Generation (RAG), and Computer Vision.

We are committed to open science: our datasets, benchmarks, and experimental resources are publicly released to support reproducible research and community-driven progress.


๐Ÿ”ฌ Research Areas

  • Data Science & Machine Learning โ€” data-driven methods, predictive models, and large-scale analytics pipelines
  • Data Profiling & Data Mining โ€” discovery of functional dependencies, metadata extraction, and incremental profiling on big data architectures
  • Information Retrieval & RAG โ€” dense retrieval, embedding benchmarking, chunking strategies, and multilingual RAG evaluation
  • Data Privacy & Social Network Analysis โ€” privacy-preserving techniques, anonymisation, and analysis of social graph structures
  • Web Engineering & Visual Languages โ€” web-based information systems, visual query languages, and multimedia databases
  • Artificial Intelligence โ€” applied AI across NLP, computer vision, and data management tasks

๐Ÿ‘ฅ Team

Giuseppe Polese

Full Professor ยท Department of Computer Science, University of Salerno
๐Ÿ“ง gpolese@unisa.it
ORCID Scholar


Stefano Cirillo

Assistant Professor (Tenure-Track) ยท Department of Computer Science, University of Salerno
๐Ÿ“ง scirillo@unisa.it ยท ๐ŸŒ UNISA page
ORCID Scholar


Giandomenico Solimando

Researcher ยท Department of Computer Science, University of Salerno
๐ŸŒ UNISA page
ORCID Scholar


๐Ÿ”— Links


If you use our datasets or find our work useful, please consider citing the relevant paper. Contributions and collaborations are welcome!

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