Jerzy Stefanowski

Main information

• My research interests
• Some of recent publications (with pdf files)
• Google Scholar list of my publications
• Curriculum Vitae
• Teaching activities - for my students (In Polish!) Some of my last courses:
•     Machine Learning (In Polish! "Uczenie maszynowe" - old course till 2020),
            A coursebook on Machine Learning (In Polish! Podręcznik - skrypt "Uczenie maszynowe i sieci neuronowe" drugie wydanie)
  
•     Zaawansowana eksploracja danych (Advanced Issues of Data Mining -- dla specjalnosci TPD semestr 2 / also in Polish! stopped teaching it)    
•     Introduction to Data Mining and Advanced Data Analysis   (Spec. Software Engineering / this course wass offered in English language only! closed in 2019)    
• Medical Informatics (In Polish! Zastosowania informatyki w medycynie / together with Krzysztof Krawiec - not offered any more).
• Grafika informacyjna (Information Visualization) (Przedmiot od 2014 do 2018)
  
• Projekt eksploracji danych (Data mining project) (Przedmiot do 2018)
  
• Seminarium problemowe - nt. metodologii prowadzania badan naukowych (Przedmiot od 2017 do 2020)
  
• System e-learning Politechniki Poznanskiej (Przedmioty dla specjalnosci mgr Sztuczna Inteligencja AI-TECH oraz anglojezycznego kierunku Sztuczna Inteligencja dostepne wylaczenie dla uprawnionych studentow - obejmuje takie przedmioty jak, np. Systemy uczace sie; Metodologia projektow badawczych, Elementy Inteligencji Obliczeniowej [wspolnie z K.Krawiec], Statystyka i Analiza Danych oraz anglojezyczne: Machine Learning, Ethics AI and Research)
  
• Tutorials on Data Mining - ALGODEC COST project

Organization of workshops, special session, journal special issues

• the First Polish Conference on Research in Artificial Intelligence (PP-RAI'2018)
• ECDA 2018: special session on Mining Streaming and Time-Evolving Data
• ISMIS 2017: Big Data Analytics and Stream Data Mining (BDASD2017)
• AMCS Journal: Special Issue on Exploring Complex and Big Data
• Odz/PAN: Processing and Mining Big Data - seminar, Poznan, April 22, 2016
• CORES 2015: 2nd Special Session on Complex Methods for Data and Web Mining
• WI 2014: Special Session on Data Stream Classification and Big Data Analytics
• CORES 2013: 1st Special Session on Complex Methods for Data and Web Mining
• CFP: Special issue of Information Science on Processing and Mining Complex Stream Data
• ICMLA 2012 Workshop : Class Imbalances: Past, Present, Future (December 2012)
• Mining Complex and Stream Data organized jointly with 16th Advanced in Databases and Information Systems Conference (ADBIS 2012).
• CFP: Combined Learning Methods and Mining Complex Data; Special Session at RSCTC'2010

Books

1. Big Data Analysis: New Algorithms for a New Society, Nathalie Japkowicz and Jerzy Stefanowski (Eds), Springer , 2016
2. Intelligent Decision Support Systems -- Combining Operations Research and Artificial Intelligence - Essays in Honor of Roman Slowinski, 2022, edited by S Greco, V Mousseau, J Stefanowski, C Zopounidis; In MCDM Series, Springer 2022
3. Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems: AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26--29, 2019, Revised Selected Papers, Joint Editorship, Springer, 2019 2019
4. Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18--22, 2017, Proceedings, Part III, Joint Editorship Springer 2017,
5. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing 11th International Conference, RSFDGrC 2007, Toronto, Canada, May 14-16, 2007. Proceedings, Spirnger, edited by Aijun An, Jerzy Stefanowski, Sheela Ramanna, Cory J. Butz, Witold Pedrycz and Guoyin Wang, 2007
6. Nowoczesne systemy informatyczne dla malych i srednich przedsiebiorstw, Piotr Adamczewski i Jerzy Stefanowski (red.) Wydawnictwo WSB Poznan 2006

Research grants

• Learning classifiers from imbalanced and evolving data NCN DEC-2013/11/B/ST6/00963; 2014-2017 (Leader)
• Algorithms transforming data representation for machine learning systems KBN 3 T11C 050 26; 2004-2007 (Leader)

Other WWW links

• Journal - Foundations of Computing and Decision Sciences -- I am Editor in Chief
• Laboratory of Intelligent Decision Support Systems
• Institute of Computing Science at Poznan University of Technology
• Faculty of Computing at PUT
• About my town - Poznan or Poznan MIM
• PSSI - Polish Artificial Intelligence Society
• Pl-SIGML - Polish Special Interest Group on Machine Learning (I am its co-founder and co-ordinator)

Research Interests:

Machine learning and data mining. Proces of knowledge discovery. Induction of decision rules, classification trees. Mutliple classifiers (ensembles). Handling imbalanced data. Data streams mining. Interpretable ML, Explanaible AI, Mining asociation rules and sequence patterns. Document clustering. Web-mining and text mining. Rough set theory. Data mining applications in medicine, technical diagnostics, financial and management problems.

Major results are concerned with:

• improving classifiers learnt from imbalanced data and identification of complexity of such data
• explaining predictions of machine learning complex models and XAI
• classification of concept drifting data streams,
• induction of various types of decision rules for discovery and classification systems,
• creating multiple (ensembles) classifiers, including generalizations of bagging and pairwise coupling (multi-class n2-classifier)
• attribute selection for classification systems,
• handling numerical data in machine learning and data mining algorithms,
• descriptive clustering of text documents and Web pages,
• mining multi-dimensional, context sequence patterns,
• rough set theory and rough set based learning systems,
• generalized rough set approach to handle incomplete data tables,
• application of machine learning and knowledge discovery approaches to medical data analysis,
  technical diagnostics, pattern recognition and financial analysis,

Other Scientific Activities:

• Member of Program Committees for conferences: ECAI 2023, SIAM Data Mining 2017, 2016, 2015; ECML/PKDD 2022, 2020 (Area Chair), 2019, 2018, 2017 (Track Chair) 2016, 2015 (Area Chair), 2014, 2013, 2011, 2008, 2007; IJCAI2020, IJCAI 2018 (Senior PC), 2017, 2015,2013; AAAI 2019, DS 2022, 2021, 2020, 2018, 2017, 2016, 2015; ISMIS 2020, 2018, 2015, 2014, 2012, 2011, 2009, 2008; DaWaK 2008, 2007, 2006; CORES 2017, 2015, 2013, CBMS 2016, JRS2014, RSCTC (all editions till 2013); RSKT 2009, 2007; KNWS (since 2006); IDA 2023; HAIS 2012, 2011; ICAISC 2017, 2016, 2015, 2014, 2010, 2008, 2006; RSEISP 2007; TPD 2007, 2005; Mini-Euro 2005; RSFDGrC 2003; IDDM-2002; SDP 2002; JSAI 2001 and many others in the past.
• One of PC Chairs of JRS 2007, Toronto. Nectar Track Co-Chair ECML/PKDD 2017, Skopje.
• Reviewed papers for journals like Journal Machine Learning Research, Machine Leaning Journal, IEEE Transactions on Data and Knowledge Engineering, ACM Transactions on Knowledge Discovery in Data, Journal of Knowledge and Information Systems, Journal of Intelligent Information Systems, IEEE Transactions on Neural Networks and Learning Systems, Information Sciences, Neurocomputing, IEEE Transactions on Cybernetics,  Transactions on Rough Sets (Member of the Editorial Board), IEEE Transactions on Fuzzy Systems, Journal of Hybrid Intelligent Systems, Journal of Applied Intelligence, Pattern Analysis and Applications, Data and Knowledge Engineering Journal, Knowledge Engineerring Review,  Journal of Multiple Criteria Decision Analysis, European Journal of Operational Research, Soft Computing, Engineering Applications of AI,  Fundamenta Informaticae, Computational Management Science, Int. Journal of Intelligent Systems in Accounting Finance and Management, Computational Intelligence, Pattern Recognition Letters and FCDS + many others.
• Reviewer of 27 Ph.D Theses and 8 Habilitations.
• Research Supervision:
  • Current Supervision of Ph.D. Students:
        An open place for new candidates
  • Past Supervision of Ph.D. Theses:
        Dawid Weiss : Descriptive Clustering as a Method for Exploring Text Collections (defended Oct 13, 2006)
        Radoslaw Ziembinski : Mining Context based Sequential Patterns (defended Sept 23, 2009)
        Krystyna Napierala : Improving Rule Classifiers for Imbalanced Data (defended March 13, 2013)
        Dariusz Brzeziński : Block-based and Online Ensembles for Concept-drifting Data Streams (defended July 7, 2015).
        Magdalena Deckert : Incremental rule learning and change detection in block based classifiers for data streams (defended November 24, 2015).
        Mateusz Lango: What makes multi-class imbalanced problems difficult? An experimental study (defended March 1, 2022).
  • I have been a supervisor of 88 Master Theses and 16 Engineering Theses since 1994.
• Editor in Chief - journal Foundations of Computing and Decision Sciences
• A corresponding member of Polish Academy of Sciences; IV Division - Engineering Sciences (elected since 2021)
• Member of Scientific Council of the Institute of Computer Science at Polish Academy of Sciences (elected since 2011)
• Member of Executive Board of Polish Artificial Intelligence Society (PSSI) since 2013
• Member of Advisory Board of Polish Artificial Intelligence Society (PSSI) since 2011
• Secretary of Executive Board of International Rough Set Society (2010-2011)
• President of Regional Wielkopolska Branch of PTI - Polish Information Processing Society (since May 2005 till 2011).

Contact

• call phone: +48 61 6652933 (my office)
• send a fax: +48 61 8771525,
• send me an e-mail message,
• or visit me at my office at the Institute of Computing Science - it is room 8 located in the building of the New Lecture Center of Poznan University of Technology.