- Current role: Senior Researcher / OPI PIB
- Specialization: artificial intelligence, natural language processing
- Core competencies: solution architecture, requirements analysis
- Profile: researcher and information systems engineer
Studies and the beginning of an engineering career
This stage covered technical studies, work on information systems, international experience through the Erasmus programme, and the first programming projects as well as self-employment.
2002–2007
Bialystok University of Technology — Electronics and Telecommunications, MSc Eng.
Studies completed with an MSc Eng. degree; the diploma thesis concerned a system for collecting and processing medical measurement data.
The project involved building a system for collecting and analysing medical data from uroflowmeters. During the studies, an Erasmus exchange at VŠB was also completed.
III 2009–X 2010
ProFind — self-employment and software development contracts
Software development, CMS, e-commerce, and internet-data-based projects.
This stage covered the full execution cycle: from architecture and implementation to maintenance and client collaboration.
Doctoral training, PhD research, and text analysis
The doctoral stage began in 2007 at Bialystok University of Technology and concluded with the dissertation defense in 2013 at the Faculty of Computer Science. The work covered text processing, knowledge representation, and information systems for public administration and emergency services.
2007–2013
Work on the doctoral dissertation — analysis of fire service reports and information system design
The research focused on transforming unstructured operational reports into data usable within an information system.
The core of the work included text segmentation, information extraction, and the design of knowledge representation rules for fire incident documentation.
2013
PhD defense
Formal completion of the research stage devoted to text data analysis in information systems.
The dissertation covered information systems, text mining, and the analysis of domain-specific documents.
IPI PAN and web information extraction
Formal collaboration took place between 2012 and 2014. The work focused on extracting information from semi-structured web pages, with an emphasis on larger-scale and more general-purpose problems. The main publication from this period — the BigGrams system — was published in 2018 with IPI PAN affiliation.
III 2012–VI 2014
Institute of Computer Science, Polish Academy of Sciences — Systems Engineer
Work on information extraction from web data and semi-structured HTML documents.
This stage extended earlier domain-focused analyses toward methods used more broadly in web mining and information extraction.
2018
BigGrams — language-agnostic information extraction from HTML
A publication devoted to information extraction from semi-structured web pages.
The publication focuses on combining processing scale, practical applicability, and relative independence from both language and page layout.
OPI PIB — development of a research-and-implementation profile
A long-term research and project stage covering text classification, document analysis, web mining, information extraction, and systems applied in public and analytical practice.
IX 2014–present
OPI PIB / AI Lab — Senior Researcher
Main center of scientific and project activity, combining research with implementation-oriented work.
This stage combines research activity with the design and development of solutions used in organizational practice.
2016–2019
Identification of innovative companies based on their websites
Automatic classification of companies in terms of innovativeness based on the content of their websites.
The project applied text classification and web mining to the automatic analysis of large collections of company websites.
2018–2020
Publications: text classification, fire service reports, SNN
Publications covering a review of text classification, information extraction from fire service reports, and biologically inspired models of text representation.
- ESWA 2018 — a synthetic review of text classification.
- Fire Technology 2019 — a publication on information extraction from fire reports.
- PPSN 2020 — a publication on neuromorphic and biologically inspired approaches to text representation.
2022–2025
ANSI / INFOSTRATEG III — detecting dual quality of products
A system analyzing multilingual online reviews in terms of product quality, safety, and dual quality issues.
The project involved crawling, data extraction, and the analysis of product reviews in the context of quality assessment and consumer protection.
Current stage: document AI, LLM, and research synthesis
The most recent stage combines the development of LLM- and RAG-based systems with publications synthesizing knowledge on document classification, multimodality, and research standards.
2024
Neural Networks and IEEE Access
Development of biologically inspired NLP methods and work focused on research quality in document classification.
Publications from this period combine the development of new NLP methods with the analysis of reporting standards and research reproducibility.
2025
ACL Industry Track — detecting dual quality in product reviews
A publication resulting from the ANSI project, devoted to the analysis of multilingual product reviews.
The publication combines a research result with practical application in the analysis of multilingual product reviews.
2025–2026
Current direction: LLM, RAG, document analysis, and knowledge transfer through the blog
The current direction covers the design of LLM-based solutions and knowledge sharing around modern AI systems.
This direction extends earlier experience in document analysis, information structure, model evaluation, and decision-support systems.
2026
Information Fusion — meta-analytical summary of document classification
A systematic review and quantitative synthesis of research on information fusion in document classification.
The publication synthesizes earlier threads concerning methodology, data representation, and multiview learning in the form of a quantitative literature review.