Tomasz Maszczyk
Nicolaus Copernicus University Tel.: (+48)(56) 6113294 Faculty of Physics, Astronomy and Informatics Mobile: (+48) 600079834 Department of Informatics Fax: (+48)(56) 6225397 Grudzi¸adzka 5, 87-100 Toru´n, Poland E-mail: [email protected] Contact
Information
Computational intelligence, artificial intelligence, cognitive informatics, Research
Interests kernel methods, data transformation, data visualization Education Nicolaus Copernicus University, Toru´n, Poland
Ph.D. in Computer Science (March 2014)
• Dissertation Topic: “Universal Learning Machines”
• Advisor: prof. W lodzis law Duch
Silesian University of Technology, Katowice, Poland M.Sc. diploma (June 2006)
• Dissertation Topic: “Analiza sk ladnik´ow g l´ownych w zastosowaniu do danych finansowych” (Principal Component Analysis applied to financial data)
• Advisor: dr Jacek Biesiada
Silesian University of Technology, Katowice, Poland M.Sc. course (2001-2006)
Technical Secondary School of Electronics, Bytom, Poland Electronics technician
Honors, awards and others
• Principal investigator in grant number 1608-F for young scientists. Grant title: De-velopment and implementation of algorithms for creating new, useful features, their integration and effective use to solve problems of classification and approximation, Toru´n, Poland 2013
• Principal investigator in grant number 1141-F for young scientists. Grant title: Development and implementation of the new machine learning methods based on deep learning mechanism used for biomedical data analysis,
Toru´n, Poland 2012
• Travel grant from Institute of Electrical and Electronics Engineers, ICONIP Doha, Qatar, 2012
• Principal investigator in grant number 407-F for young scientists. Grant title: Ma-chine learning methods based on generation, transformation, feature selection and transfer learning, 2011
• Step into the future – scholarship for PhD students (from European Union) Toru´n, Poland 2010
• Travel grant from European Neural Network Society, ICANN Limassol, Cyprus, 2009
• Travel grant from European Neural Network Society, ICANN Prague, Czech Republic, 2008
• Third place in Metallurgical Process Regression Modeling (ICAISC competition) Zakopane, Poland 2008
• Participation in grant number N N516 442138 as contractor.
Principal investigator - dr Marcin Blachnik. Grant title: Rule-based systems based on prototypes and their application to the analysis of experimental data
• Participation in grant number N N516 500539 as contractor.
Principal investigator - dr Norbert Jankowski. Grant title: Universal meta-learning algorithms in computational intelligence
• Co-author of Intelligent Expert System (ISE), 2008
Publications • Tomasz Maszczyk and W lodzis law Duch. Recursive Similarity-Based Algorithm for Deep Learning. In Tingwen Huang, Zhigang Zeng, Chuandong Li and Chi Sing Leung, editors, ICONIP, volume 7665 of Lecture Notes in Computer Science, pages 390-397. Springer, 2012.
• Marcin Blachnik, W lodzis law Duch and Tomasz Maszczyk. Feature ranking methods used for selection of prototypes. In Alessandro Villa, W lodzis law Duch, Peter Erdi, Francesco Masulli and Gunther Palm, editors, ICANN, volume 7553 of Lecture Notes in Computer Science, pages 296-304. Springer, 2012.
• W lodzis law Duch, Norbert Jankowski and Tomasz Maszczyk. Make it cheap: learn-ing withO(nd) complexity. In IJCNN, pages 1–4. IEEE Press, 2012.
• Tomasz Maszczyk and W lodzis law Duch. Locally optimized kernels. In Leszek Rutkowski, Marcin Korytkowski, Rafa Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh and Jacek M. Zurada, editors, ICAISC, volume 7267 of Lecture Notes in Computer Science, pages 412–420. Springer, 2012.
• W lodzis law Duch, Tomasz Maszczyk and Marek Grochowski. Optimal Support Fea-tures for Meta-Learning. In Norbert Jankowski, W lodzis law Duch and Krzysztof Gr¸abczewski, editors, Meta-Learning in Computational Intelligence, volume 358 of Studies in Computational Intelligence, pages 317–358. Springer, 2011.
• Tomasz Maszczyk, Marek Grochowski, and W lodzis law Duch. Discovering data structures using meta-learning, visualization and constructive neural networks. In Jacek Koronacki, Zbigniew W. Ras, Slawomir T. Wierzchon, and Janusz Kacprzyk, editors, Advances in Machine Learning II, volume 263 of Studies in Computational Intelligence, pages 467-484. Springer, 2010.
• Tomasz Maszczyk and W lodzis law Duch. Almost Random Projection Machine with Margin Maximization and Kernel Features. In Konstantinos I. Diamantaras, Wlodek Duch and Lazaros S. Iliadis, editors, ICANN (2), volume 6353 of Lecture Notes in Computer Science, pages 40-48. Springer, 2010.
• Tomasz Maszczyk and W lodzis law Duch. Support Feature Machine for DNA Mi-croarray Data. In Marcin Szczuka, Marzena Kryszkiewicz, Sheela Ramanna, Richard Jensen and Qinghua Hu, editors, RSCTC, volume 6086 of Lecture Notes in Com-puter Science, pages 178-186. Springer, 2010.
• Tomasz Maszczyk and W lodzis law Duch. Triangular visualization. In Leszek Rutkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh and Jacek M. Zurada, edi-tors, ICAISC, volume 6113 of Lecture Notes in Computer Science, pages 445–452. Springer, 2010.
• Tomasz Maszczyk and W lodzis law Duch. Support Feature Machines: Support Vec-tors are not enough. In WCCI, pages 3852–3859. IEEE Press, 2010.
• W lodzis law Duch and Tomasz Maszczyk. Universal learning machines. In Chi-Sing Leung, Minho Lee, and Jonathan Hoyin Chan, editors, ICONIP (2), volume 5864 of Lecture Notes in Computer Science, pages 206-215. Springer, 2009.
• W lodzis law Duch and Tomasz Maszczyk. Almost random projection machine. In Cesare Alippi, Marios M. Polycarpou, Christos Panayiotou, and Georgios Ellinas, editors, ICANN (1), volume 5768 of Lecture Notes in Computer Science, pages 789-798. Springer, 2009.
• Tomasz Maszczyk and W lodzis law Duch. Comparison of Shannon, Renyi and Tsallis entropy used in decision trees. In Leszek Rutkowski, Ryszard Tadeusiewicz, Lotfi A. Zadeh, and Jacek M. Zurada, editors, ICAISC, volume 5097 of Lecture Notes in Computer Science, pages 643-651. Springer, 2008.
• Tomasz Maszczyk and W lodzis law Duch. Support vector machines for visualization and dimensionality reduction. In Vera Kurkov, Roman Neruda, and Jan Koutnk, editors, ICANN (1), volume 5163 of Lecture Notes in Computer Science, pages 346-356. Springer, 2008.
Conferences • International Conference on Neural Information Processing, Doha, Qatar, 12–15 November, 2012
• International Conference on Artificial Neural Networks, Lausanne, Switzerland, 11–14 September, 2012
• International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland,
29 April – 3 May, 2012
• International Conference on Artificial Neural Networks, Thessaloniki, Greece, 15–18 September, 2010
• World Congress on Computational Intelligence, Barcelona, Spain, 18–23 July, 2010
• 7th International Conference on Rough Sets and Current Trends in Computing, Warsaw, Poland,
28–30 June, 2010
• International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland,
13–17 June, 2010
• International Conference on Artificial Neural Networks, Limassol, Cyprus, 14–17 September, 2009
• International Conference on Artificial Neural Networks, Prague, Czech Republic, 3–6 September, 2008
• International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland,
22–26 June, 2008
• Body, perception and awareness, Toru´n, Poland, 23–25 November, 2009
• Argumentation as a Cognitive Process, Toru´n, Poland, 15–17 May, 2008
• Enactivism: a new paradigm, Toru´n, Poland, 6–8 October, 2008
• Third Ethics and Science for Environment Forum, Toru´n, Poland, 12–14 October, 2008
• See how the brain works, Warsaw, Poland, 13 October, 2007
• Self, Intersubjectivity and Social Neuroscience: From Mind and Action to Society, Toru´n, Poland,
24–26 September, 2007
• The second congress of network security, Warsaw, 27–28 February, 2006
• Linux Autumn, Ustro´n, Poland, 28-30 October, 2005
• Statistics and data mining in scientific research, Warsaw, Poland, 24 October, 2005
• Microsoft SQL Server, Katowice, Poland, 6 October, 2005
International Conference on Artificial Neural Networks– Hamburg, Germany Scientific
committee 15–19 September, 2014
World Congress on Computational Intelligence – ALML: International Work-shop on Advances in Learning from/with Multiple Learners, Beijing, China
6–11 July, 2014
International Joint Conference on Neural Networks– IML’2013: Special Session on Incremental Machine Learning: Methods and Applications, Dallas, Texas, USA 4–9 August, 2013
Machine Learning Summer School– National University of Singapore, Singapore Workshops
13–17 June, 2011
Summer School on Neural Networks in Classification, Regression and Data Mining– Polytechnic School of Engineering of Porto, Porto, Portugal
7–11 July, 2008
Summer School in Statistical Learning, Data mining and Regression Tools– Second University of Naples, Terra Murata - Island of Procida, Italy
3–7 July, 2007
Nicolaus Copernicus University, Professional
experience Grudziadzka 5, 87-100, Toru´n, Poland
Teaching and research assistant (October, 2006 – present)
My duties include scientific research in Computer Science, leading weekly lectures and computer lab exercises with students.
NEUCA,
Szosa Bydgoska 58, 87-100, Toru´n, Poland
SPIN internship - Consistency of Business and Science (October, 2010 – December, 2010)
My duties included creation of a system to predicting financial potential of pharma-ceutical stores.
Central Mining Institute,
Plac Gwark´ow 1, 40-166, Katowice, Poland
Expert of computational intelligence methods (July, 2005 – December, 2008)
My duties included creation of a system to predicting geometrical changes of the mining tunnel.
Silesian University of Technology,
Zygmunta Krasi´nskiego 13, 40-019, Katowice, Poland System Administrator (October, 2005 – June, 2006)
My duties include taking care of faculty computer system (setting up the network, installation of software and hardware).
Teaching experience
• Computational Intelligence, programming models, tools
• Windows Server Administration Course, administration, networking
• Object-oriented Programming, C++ programming, tools
• Programming Languages, languages basics, tools, libraries
• C programming, language, tools
• Introduction to Informatics, basic computer usage
Abilities • Languages: Polish (mother tongue), English (advanced)
• Computer languages: C, C++, C#, LATEX, Matlab, Pascal, PHP
• Operating systems: Linux, Windows (usage and administration – certificate)
• Other computer skills: Asp.Net, HTML, Microsoft Office, SQL
