About me

I am an Assistant Professor at the University of Helsinki in Finland, where I lead a research group on Data science and evolution. I am also affiliated with the Finnish Museum of Natural History (LUOMUS).


I am/have been involved in these funded projects:

Professional Activities

Editorial activities

Program Committee Membership

KDD-applied'19, NeurIPS'19, MACLEAN2019, IoT-Stream'19

ECMLPKDD'18, DSDAH'18, IDA18, IOTSTREAM18, KDD'18-applied,

ECMLPKDD'17 (Area Chair), SAC'17 - Data Streams,

IDA'15, IDA'16, IVUS'16, ECMLPKDD'16, PhDforum@ICDM'16,


ECMLPKDD'13, IJCAI'13, IVUS'13, PROMAMEDS'13@CBMS, SAC'13 - Data Streams, COPEM'13@ECMLPKDD, ICDM'13 PhD student forum,


CIDUE'11, ECMLPKDD'11, FSKD'11, HAIS'11, IJCAI'11, ISDA'11, SAC'11-Data Streams,

CBMS'10, FSKD'10, IVUS'10

Reviewing for journals

  • Ecology Letters (2019)
  • Palaeogeography, Palaeoclimatology, Palaeoecology (2019)
  • Nature (2019)
  • Data Mining and Knowledge Discovery, Springer (2013-2019)
  • Machine Learning, Springer (2012-2019)
  • Pattern Recognition, Elsevier (2009-2013, 2019)
  • International journal of computer vision (2019)
  • Palaeobiodiversity and Palaeoenvironments (2018)
  • Artificial intelligence review (2017)
  • Scientific Reports (2017)
  • Evolutionary Ecology Research (2016)
  • PLOSI (2016)
  • ACM Transactions on Knowledge Discovery from Data (2016)
  • IEEE Transactions on Knowledge and Data Engineering (2014-2017,2019)
  • IEEE Transactions on Learning Technologies (2015)
  • Journal of Machine Learning Research (2013)
  • Artificial Intelligence and Law, Springer (2013)
  • IEEE Transactions on Neural Networks and Learning Systems (2010-2013,2015-2018)
  • Knowledge Information Systems, Springer (2011-2013,2016,2018)
  • Information Sciences, Elsevier (2011-2013)
  • Information Systems, Elsevier (2011-2012,2015)
  • Computational Statistics and Data Analysis, Elsevier (2012)
  • Journal of Intelligent Information Systems, Springer (2012)
  • Evolving Systems, Springer (2012)
  • Neurocomputing, Elsevier (2012, 2018)
  • International Journal of Tourism Research, Wiley (2012)
  • IEEE Transactions on Cybernetics (2012, 2018)
  • Intelligent Systems in Accounting, Finance and Management, Wiley (2011)
  • Advances in Data Analysis and Classification, Springer (2010)
  • Journal of Pattern Recognition Research (2009-2010)
  • Pattern Recognition Letters, Elsevier (2009)
  • Central European Journal of Computer Science (2013)
  • European Journal of Operational Research, Elsevier (2008-2009)
  • Journal of Graphical and Computational Statistics, ASA (2008)

Reviewing for funding

  • Estonian Research Council

Workshop organization

  • Co-Chair of RealStream (Real-World Challenges for Data Stream Mining) workshop at ECMLPKDD'13
  • Co-Chair of DPADM (Discrimination and Privacy Aware Data Mining) workshop at ICDM'12
  • Co-Chair of HaCDAIS'11 workshop at ICDM'11 in Vancouver, Canada
  • Co-organizer of INFER-APS'11 workshop in Bournemouth, UK
  • Co-Chair of HaCDAIS'10 workshop at ECMLPKDD'10 in Barcelona, Catalonia, Spain
  • Co-organizer of DHDHD'10 workshop in Eindhoven, the Netherlands

Tutorials given

Advanced Topics in Data Stream Mining at ECMLPKDD'12

tutorialists: A. Bifet, J. Gama, R. Gavalda, G. Krempl, M. Pechenizkiy, B. Pfahringer, M. Spiliopoulou, I. Žliobaitė

Handling Concept Drift: Importance, Challenges and Solutions at PAKDD'11

tutorialists: A.Bifet, J.Gama, M. Pechenizkiy, I. Žliobaitė

Handling Concept Drift, in Medical Applications: Importance, Challenges and Solutions at CBMS'10

tutorialists: M. Pechenizkiy, I. Žliobaitė

Learning from Evolving data at ECMLPKDD'10

tutorialists: M. Spiliopoulou, J. Gama, E. Menasalvas, A. Vakali, guest speakers: M. Pechenizkiy, I. Žliobaitė

Invited and Seminar Talks


  • Predictive modeling over evolutionary times at CS Forum, Aalto University slides
  • Teeth, diet and environment: some insights into why ecometrics works at Kurten Club, University of Helsinki


  • Ecometrics: reconstructing climate of the past via teeth at University of Oslo
  • The Law of constant Extinction revisited at CEES Oslo


  • Ecometrics beyond limits at Kurtén Club, University of Helsinki slides


  • Adaptive learning from evolving data at CEES Oslo
  • How can decision making by algorithms discriminate people, and how to prevent that at Centre for Research Methods, University of Helsinki slides
    • Can algorithms discriminate? at EU Fundamental Rights Agency, Vienna, Austria slides
  • Can machines discriminate? and how to avoid that, HIIT seminar, Finland slides
  • Pitfalls to avoid in data analysis, Björn Kurtén Club, University of Helsinki


  • Regression models for data streams with missing values, LIAAD-INESC TEC, Portugal


  • Predictive modeling for streaming data, ENVI summer-seminar, University of Eastern Finland, Finland
  • Real-world challenges for mining streaming data:lessons learned in chemical industry, HIIT seminar, Finland
  • Mining Evolving Data Streams: challenges and lessons learned in chemical industry, King Abdullah University of Science and Technology, Saudi Arabia


  • Towards implementation of an adaptive soft sensor, Evonik Industries, Germany
  • Active learning from evolving streaming data
  • Adaptive learning from drifting data, University of Konstanz, Germany slides


  • Active learning with evolving data, Eindhoven University of Technology, the Netherlands slides
  • Adaptive pre-processing for streaming data, Workshop on Recent Trends in Machine Learning and Data Mining at UPC Barcelona
  • Controlled Permutations for Testing Adaptive Classifiers
    • Bangor University, UK
    • The University of Birmingham, UK. slides
    • Katholieke Universiteit Leuven, Belgium. slides
    • University of Waikato, New Zealand. slides


  • Computational Intelligence and Machine Learning Methods for Adaptive Prediction Systems, Bournemouth University, UK.
  • Learning with actionable attributes
    • TU Eindhoven slides
    • UPC Barcelona slides
    • University of Waikato, New Zealand slides
  • Learning from Evolving Data: an application perspective. Tutorial block with M.Pechenizkiy at ECML/PKDD. slides
  • Identifying hidden contexts. DHDHD workshop, TU Eindhoven. slides
  • Mokymas besikeičiančioje aplinkoje
    • Vilniaus universitetas, seminaras. slides
    • Matematikos ir informatikos institutas, seminaras.
    • Vytauto Didžiojo universitetas, seminaras.


  • Training Instance Selection under Concept Drift
    • TU Eindhoven, invited talk. slides
    • Helsinki University of Technology (HUT), Statistical Machine Learning and Bioinformatics group, seminar.


  • Pattern Recognition in the Presence of Concept Drift. Bangor University (UK), School of Computer Science, seminar. slides


  • Pattern Recognition under Concept Drift. Druskininkai, Modern Data Mining Technologies, summer school.