About Us

The Department's staff conduct scientific research in international teams, and their work is published in reputable journals (including Information Sciences, VLDB Journal, Expert Systems with Applications, Information Systems, Data & Knowledge Engineering, Information Systems Frontiers, Scientific Reports, Semantic Web Journal, Journal of Web Semantics) and presented at international conferences (including World Wide Web, Association of Computational Linguistics, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Neural Information Processing Systems, Advances in Databases and Information Systems, International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data, Extended Semantic Web Conference, Knowledge Capture Conference, Knowledge Engineering and Knowledge Management, International Conference on Information and Knowledge Management, as well as SIGMOD and EDBT/ICDT workshops).

The department is led by dr hab. inż. Robert Wrembel, prof. PUT

Department employees

Research

The research currently conducted at the Department includes:

• Data quality in large repositories (including data cleansing and duplicate detection),
• Application of statistical methods and machine learning for detecting duplicate record groups,
• Optimization of multimodal data integration processes,
• Performance modeling of programs treated as black boxes,
• Spatial data collocations,
• Natural language processing techniques,
• Text classification techniques,
• Methods for building and managing ontologies and knowledge graphs.

The Department's staff also collaborate with industry partners, carrying out joint research and development projects (e.g., for PKO BP, Kogeneracja Zachód, Samsung Electronics Poland, Syndigo). In recent years, they have completed the following scientific and R&D projects:

• 2022-2025: Produktoskop – development of an information system using AI to identify consumer opinions on product safety and quality; funded by NCBiR, INFOSTRATEG-III/0003/2021-00.
• 2020-2023: Models and techniques for managing the correctness and timeliness of master data on customers/citizens in a large financial institution using self-learning modeling; funded by NCBiR and PKO BP, POIR.01.01.01-00-0287/19.
• 2021-2023: TAISTI – Development of a technology based on artificial intelligence for inferring substitutable recipe ingredients; funded by Norway Grants via NCBiR under the Small Grant Scheme, NOR/SGS/TAISTI/0323/2020.
• 2019: Research agenda on predictive models for energy production and demand; funded by Kogeneracja Zachód.
• 2019: Design and optimization of big data integration architectures; funded by the Bekker NAWA grant.
• 2013-2019: Erasmus Mundus Joint Doctorate on Information Technologies for Business Intelligence (IT4BI-DC); funded by the European Commission, grant no. 2013-0038.
• 2016-2019: Analytical and exploratory processing of sequential data: models, algorithms, and data structures; funded by NCN, grant no. 2015/19/B/ST6/02637.
• 2020-2024: #Cyber_resilience: How can online social networks build resilience against disinformation?; funded by NCN, grant no. 2019/35/J/HS6/03498.