Supervisors from Institute of Computer Science

 ldebowsk@ipipan.waw.pl

@ https://home.ipipan.waw.pl/l.debowski/

Łukasz Dębowski obtained his MSc in theoretical physics from the University of Warsaw in 1994, his PhD in computer science from the Polish Academy of Sciences in 2005, and his Dsc (habilitation) in computer science from the Polish Academy of Sciences in 2015. He visited the Institute of Formal and Applied Linguistics at Charles University in 2001, Santa Fe Institute in 2002, the School of Computer Science and Engineering at the University of New South Wales in 2006, the Centrum Wiskunde & Informatica from 2008 to 2009, and the Department of Advanced Information Technology at Kyushu University in 2015. He is currently an associate professor at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS). He is a member of the International Quantitative Linguistics Association.

 

Research interests:

Information theory, statistics, natural language engineering

 

Major publications:

Dębowski Ł. (2020). “Approximating Information Measures for Fields”. Entropy, vol. 22(1), pp. 79. https://doi.org/10.3390/e22010079.

Dębowski Ł. (2018). “Maximal Repetition and Zero Entropy Rate”, IEEE Transactions on Information Theory, vol. 64(4), 2212–2219. https://doi.org/10.1109/TIT.2017.2733535.

Dębowski Ł. (2018). “Is Natural Language a Perigraphic Process?”, The Theorem about Facts and Words Revisited. Entropy, vol. 20(2), 85. https://doi.org/10.3390/e20020085.

Dębowski Ł. (2017). “Regular Hilberg Processes: An Example of Processes with a Vanishing Entropy Rate”, IEEE Transactions on Information Theory, vol. 63(10), 6538–6546. https://doi.org/10.1109/TIT.2017.2734655.

Takahira, K. Tanaka-Ishii, Dębowski Ł. (2016). “Entropy Rate Estimates for Natural Language – A New Extrapolation of Compressed Large-Scale Corpora”, Entropy, vol. 18(10), 364. https://doi.org/10.3390/e18100364.

 miel@ipipan.waw.pl

@ https://home.ipipan.waw.pl/j.mielniczuk/

Jan Mielniczuk is a full professor and head of the Department of Artificial Intelligence at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS) and professor at the Faculty of Mathematics and Information Science, Warsaw University of Technology. He earned his PhD (1985) from the Warsaw University and his DSc (habilitation) degree (1996) from ICS PAS. In 2009 he received title of professor. His main research contributions concern computational statistics and data mining, in particular time series modelling and prediction, inference for high-dimensional and misspecified data, model selection, asymptotic analysis and quantification of dependence. He is an author of two books and over seventy articles in major machine learning and statistical journals. He is an elected member of the Committee on Mathematics, Polish Academy of Sciences.

 

Research interests:

Model selection, dependence analysis, regression models, information theory.

 

Major publications:

Kubkowski M., Mielniczuk J. (h2020). “Asymptotic distributions of empirical interaction information”, Methodology and Computing in Applied Probability, https://doi.org/10.1007/s11009-020-09783-0.

Teisseyre P., Mielniczuk J., Łazęcka M. (2020). “Different strategies of fitting logistic regression for positive and unlabelled data”, Proceedings of the International Conference on Computational Science ICCS’20.

Mielniczuk J., Teisseyre P. (2019). “Stopping rules for mutual information-based feature selection”, Neurocomputing, 358, 255-274.

Pokarowski P. Mielniczuk J. (2015). “Combined l_1 and greedy l_0 least squares for linear model selection”, Journal of Machine Learning Research, 16, 961-992.

Mielniczuk J., Zhou Z., Wu W. B. (2009). “On nonparametric prediction of linear processes”, Journal of Time Series Analysis,30,163-187.

 maciej.ogrodniczuk@ipipan.waw.pl

@ http://zil.ipipan.waw.pl/MaciejOgrodniczuk

Maciej Ogrodniczuk is an associate professor at the Institute of Computer Science, Polish Academy of Sciences (ICS), where he leads the Linguistic Engineering Group. He earned his MSc in computer science from the University of Warsaw in 2000, his PhD in computational linguistics from the University of Warsaw in 2006 and his DSc (habilitation) in computer science from the Polish Academy of Sciences in 2019. He has managed several national and international projects in the field of natural language processing.

 

Research interests:

Corpus linguistics, language tools and resources, coreference resolution.

 

Major publications:

Ogrodniczuk M., Górski R. L., Łaziński M., Pęzik P. (2019). “From the National Corpus of Polish to the Polish Corpus Infrastructure”, Jazykovedný časopis 70(2):315–323, https://doi.org/10.2478/jazcas-2019-0061.

Kieraś W., Kobyliński Ł., Ogrodniczuk M. (2018). “Korpusomat — a tool for creating searchable morphosyntactically tagged corpora”, Computational Methods in Science and Technology 24(1):21–27, https://doi.org/10.12921/cmst.2018.0000005.

Ogrodniczuk M. (2018). “Polish Parliamentary Corpus”, In Proceedings of the LREC 2018 Workshop ParlaCLARIN: Creating and Using Parliamentary Corpora, pp. 15–19, ELRA. http://lrec-conf.org/workshops/lrec2018/W2/summaries/11_W2.html.

Ogrodniczuk M., Głowińska K., Kopeć M., Savary A., Zawisławska M. (2015). “Coreference in Polish: Annotation, Resolution and Evaluation”, Walter De Gruyter. http://www.degruyter.com/view/product/428667.

Ogrodniczuk M, Kopeć M. (2014). “The Polish Summaries Corpus”, Proceedings of the 9th International Conference on Language Resources and Evaluation, pp. 3712–3715, ELRA. https://www.aclweb.org/anthology/L14-1145/.

 piotr.przybyla@ipipan.waw.pl

@ https://home.ipipan.waw.pl/p.przybyla/

Piotr Przybyła earned his PhD in computer science from the Institute of Computer Science, Polish Academy of Sciences (ICS PAS) in 2015, based on work in natural language processing, especially question answering. Subsequently he spent 3.5 years at the University of Manchester as a research associate and a research fellow, where he focused on the biomedical applications of machine learning and text mining. Currently he is an assistant professor at ICS PAS, where he is carrying out a research project on the automatic assessment of text credibility, especially in the context of social and news media.

 

Research interests:

Natural language processing, text classification, biomedical NLP, misinformation.

 

Major publications:

Przybyła P. (2020).“Capturing the Style of Fake News,” in Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, USA.

Przybyła P., Brockmeier A. J., Ananiadou S. (2019). “Quantifying risk factors in medical reports with a context-aware linear model,” Journal of the American Medical Informatics Association, vol. 26, issue 6, 537-546.

Przybyła P., Brockmeier A. J., Kontonatsios G., Le Pogam M., McNaught J., von Elm E., K. Nolan, Ananiadou S. (2018). “Prioritising references for systematic reviews with RobotAnalyst: A user study,” Research Synthesis Methods, vol. 9, no. 3: 470-488.

 drabent@ipipan.waw.pl

@ home.ipipan.waw.pl/w.drabent/

Włodek Drabent works at the Institute of Computer Science, Polish Academy of Sciences (ICS PAS), where he has been a professor since 2011. He is also a (part time) visiting professor at Linköping University, Sweden. He earned his PhD in computer science from Warsaw University of Technology, and his DSc (habiltiation) in mathematics / computer science from the Institute of Computer Science PAS. He has been a program committee member oforf around 25 international conferences, mainly related to logic programming. He has published papers with more than 25 co-authors.

 

Research interests:

Logic programming (LP), in particular – semantics, reasoning about program properties, locating errors in programs, negation and other extensions of the basic LP paradigm. Also, semantics of programming languages and program correctness.

 

Major publications:

Drabent W. (2018). Logic + control: On program construction and verification. Theory and Practice of Logic Programming 18(1):1-29. DOI: 10.1017/S1471068417000047.

Drabent W. (2016). Correctness and Completeness of Logic Programs. ACM Transactions on Computational Logic 17(3), Article 18 (May 2016), 32 pages. DOI: 10.1145/ 2898434.

Drabent W. (2016). On definite program answers and least Herbrand models. Theory and Practice of Logic Programming 16(4):498-508. DOI: 10.1017/S1471068416000089.

Drabent W., Małuszyński J. (2010). Hybrid Rules with Well-Founded Semantics. Knowledge and Information Systems 25(1):137-168. DOI: 10.1007/s10115-010-0300-5.

Drabent W., Miłkowska M. (2005). Proving Correctness and Completeness of Normal Programs – a Declarative Approach. Theory and Practice of Logic Programming 5(6):669-711, 2005. DOI: 10.1017/S147106840500253X.

Drabent W. (1996). Completeness of SLDNF-resolution for non-floundering queries. The Journal of Logic Programming, 27(2):89-106. DOI:10.1016/0743-1066(95)00118-2.

Drabent W. (1995). What is failure? An Approach to Constructive Negation. Acta Informatica, 32(1):27-59. DOI:10.1007/BF01185404.

Drabent W., Nadjm-Tehrani S., Małuszyński J. (1989). Algorithmic debugging with assertions. In H.Abramson and M.H.Rogers, editors, Meta-Programming in Logic Programming, chapter 26, pages 501-522. The MIT Press.

Drabent W., Małuszyński J. (1988). Inductive Assertion Method for Logic Programs. Theoretical Computer Science, 59:133-155.

Drabent W. (1997). A Floyd-Hoare Method for Prolog. Linköping Electronic Articles in Computer and Information Science Vol.2: nr 013.

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