Research we provide

Sentiment Analysis

Is an opportunity to discover business value in opinions, emotions, and attitudes in social media, news, and enterprise feedback.

Multi-label classification

Improving multi-label classification with novel approaches to label space division.

Spread of Influence

When one's emotions, opinions, or behaviors are affected by others.

Big Data

We provide Analytics based on digital data of unusual size (beyond the capacity of a traditional database).

Complex Networks

Analysis of complex networks built based on different type of sources: social media, mails, researcher's collaboration, citations, textual data, power grids, biological data etc.

Machine Learning

How to build the Artificial Intelligence (AI) systems that provides computers with the ability to learn without being explicitly programmed?

Distributed Computing

Can we leverage distributed computing for machine learning and predictive analytics?

Social Media Analysis

Social media analytics is the practice of gathering data from blogs and social media websites and analyzing that data to make business decisions or check psychological hypothesis.

Social Network Analysis

Social network analysis is focused on uncovering the patterning of people's interaction.

Recent Publications

Meet the Team

Przemysław Kazienko


Piotr Bródka

Assistant Professor

Tomasz Kajdanowicz

Assistant Professor

Radosław Michalski

Assistant Professor

Łukasz Augustyniak

Ph.D. Student

Roman Bartusiak

Ph.D. Student

Rajmund Klemiński

Ph.D. Student

Marcin Kulisiewicz

Ph.D. Student

Stanisław Saganowski

Ph.D. Student

Piotr Szymański

Ph.D. Student

Włodzimierz Tuligłowicz

Ph.D. Student

Marek Żuk

Technology Transfer Officer

Olla Kijaczko-Dereń

Project Management Office

Monika Sawicka

Project Management Office

Monika Skawińska

Project Management Office



Project European research Centre of Network intelliGence for Innovation Enhancement, Framework Programme 7 of the EU.

Grant number: 316097, FP7-REGPOT-2012-2013-1

Date: 1st March 2010 to 31 September 2016

Budget: €4,245,000


Reverse EngiNeering of sOcial Information pRocessing, EU Horizon2020 Project in the framework of Marie Skłodowska-Curie Actions, Research and Innovation Staff Exchange (RISE)

Call:: H2020-MSCA-RISE-2015

Date: 1st January 2016 to 31 December 2019

Budget: €1,314,000


TRANSFoRm - Translational Research and Patient Safety in Europe

Grant number: FP7 247787

Date: 1st March 2010 to 30 November 2015

Budget: €9,726,688
EU Contribution: €7,540,000

PLGRID NG Complex Networks

Building Big Data Analytics tool for processing networks and textual data. Cooperation with Wroclaw Centre for Networking and Supercomputing in Polish National Grid Initiative.

Machine Learning Methods for Complex Networks

The project aims to develop new, better methods of machine learning specialized for relational data, in particular for complex networks. Research grant funded by National Science Centre.

Alior Bank S.A

Big Data for Clients’ value assessment for debt purposes (2013) Alior Bank S.A.

Research project founded by Polish National Science Center

Data mining in complex social network systems (2010-2013) – Research project founded by Polish National Science Center


Machine Learning Algorithms for DSL service recommendation (2012) – Design and implementation of hybrid decision support system with new classification algorithms for maximization of broadband service access for Orange Poland.

Kruk S.A

Debt portfolio valuation (2011-2012) – Design and implementation of adaptive method for debt portfolio valuation based on structured output prediction for Kruk S.A. – the biggest East European debt collection company.

Data mining in complex social network systems

The main objective of this project is to develop new data mining methods that will allow for analysis large, dynamic and complex social networks. Based on the analysis of both static and dynamic complex social networks will be built, a generic model for tracing, interpretation and prediction of behavioral changes of network’s users.


Groups, Relationships and Activities in the criminal networks, 2009-2011 – The main objective of the GRASP # project was to establish a prototype system for the analysis of interpersonal relationships resulting from the large amounts of data on mutual communication, joint activities and direct connections with the use of advanced methods of data mining and other analytical methods applied to the network society.

British Telecom

Social Networks in Telecommunication – in co-operation with British Telecom, Intelligent Systems Research Centre (ISRC), 2007-2010.