Research

Research Interests

1. Machine Learning

Structured Prediction, Multilabel Classification, Multiple Classifier Systems, Pattern Recognition, Machine Learning, Knowledge Discovery in Databases (KDD), Data Mining, Data Warehousing

2. Social Network Analysis

Classification in Social Networks, Social Networks Analysis, Social Networks Applications

3. Data mining and Predictive Analytics

Fraud Detection Systems

4. Project management techniques

Estimation and Calibration Techniques for Project Planning, Parametric and Goal Oriented Project Optimization

5. Complex Information Systems Design, Integration and Interoperability

Service Oriented Systems Architecture, Efficient Integration of Complex Information Systems

6. Computational methods for medical data analysis

Data Mining techniques specialized for health care environment, Mobile eHeath online prediction

7. Big data

Development of Data Mining techniques for efficient processing of large data

Research & Development Projects

Engine - European research Centre of Network intelliGence for INnovation Enhancement (2013-2016)

Establishment of a New Complex Networks and Massive Data Analysis Laboratory, organization of workshops, collaboration with visiting professors

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

TRANSFoRm - Translational Research and Patient Safety in Europe (2012-2015)

Decision support systems for primary care, project supported by European Union, FP7

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

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

Sequential structured prediction using machine learning methods, 2011-12

The main objective of this project is to develop new prediction methods based on ensembles of models

for structured outputs like sequences. Proposed algorithms will allow solving problems such as debt recovery prediction, protein classification, semantic image classification or text categorization. The project is supported by The Polish Ministry of Science and Higher Education and Science research grant.

Data mining in complex social network systems, 2010-2013

The main objective of this project is to develop new data mining methods that will allow for analysis of 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. Exploring the relationship between people, profiles of users and their activity will eventually lead to knowledge which is not available directly to individuals. Data mining in complex social network systems is supported by The Polish Ministry of Science and Higher Education and Science research grant, 2010-13 and is realized in cooperation with Poznan University of Technology and AGH University of Science and Technology.

Grasp# (Groups, Relationships and Activities in the criminal networks), 2009-2011The main objective of the GRASP # project is to establish a prototype system for the analysis of interpersonal relationships resulting from thelarge amounts of data on mutual communication, joint activities and direct connections with the use of advanced methods of data miningand other analytical methods applied to the network society. The project is supported by The Polish Ministry of Higher Education and Science and is developed jointly with Research & Engineering Center REC and Telnet.

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

  1. Course "data mining" at Friedrich Alexander Universität, Erlangen-Nürnberg, Germany, 2009