Short Biography

Mykola Pechenizkiy Mykola Pechenizkiy is Full Professor and Chair of the Data Mining research group that is part of the Information Systems Section at the Department of Computer Science, Eindhoven University of Technology (TU/e), the Netherlands. He received his PhD (“Feature Extraction for Supervised Learning in Knowledge Discovery Systems”) from the Computer Science and Information Systems department at the University of Jyväskylä, Finland in 2005. In 2006, after a short postdoc he joined TU/e as Assistant Professor; later in 2015 and 2016 he became Associate Professor and Full Professor correspondingly. His collaboration with the University of Jyväskylä continued; since 2013 he is Adjunct Professor (Dosentti) in Data Mining for Industrial Applications at the Department of the Mathematical Information Technology there. At the Data Science Center Eindhoven Prof. Pechenizkiy leads the Customer Journey interdisciplinary research program aiming at developing techniques for informed and responsible analytics. His core expertise and research interests are in predictive analytics and knowledge discovery from evolving data, and in their application to real-world problems in industry, medicine and education. He has been a principal investigator of several nationally funded projects, including NWO RATE Analytics, NWO HaCDAIS, STW CAPA, and Surf CoDAK and Surf CurriM. Through these projects being inspired by challenges of the real-world applications he develops foundations for next generation predictive analytics. Prof. Pechenizkiy has actively collaborated on this with industry through EU-, nationally- and industry-funded projects, including EIT ICT Labs Stress@Work, NL Agency CoDAK, Rabobank KYC as well as through numerous external MSc thesis projects, e.g. with Adversitement, ASML, Betabit, C-Content, Coosto, IMEC, Microsoft, Multiscope, NLR, Oce, Philips Lighting, Philips Research, PSV, Rabobank, Sanoma Media Group, Sligro Food Group, StudyPortals, and Teezir. Prof. Pechenizkiy was on visiting research to several universities, including Aalto U., U. Bournemouth, Columbia U., U. Cordoba, New York U., U. Porto, U. Technology Sydney, Trinity College Dublin, and U. Ulster. Over the past decade he has co-authored more than 100 peer-reviewed publications. He has been also actively involved in organizing several successful conferences, thematic workshops and special issues with journals. He regularly serves on several program committees of leading data mining and AI conferences, including AAAI, IJCAI, ECMLPKDD, EDM, LAK, IDA, DSAA, DS, AISTATS, NIPS, SDM and editorial boards of DAMI, IEEE TLT and JEDM journals. He serves as the President of IEDMS, the International Educational Data Mining Society. As a panelist and an invited speaker he has been advocating for the responsible data science and ethics-aware predictive analytics research at several events, including the FATML@ICML 2015 and NSF IRB Privacy and Big Data workshops and the EDM 2015 conference.

Last update: October 2017

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