1. shifting from blind reactive adaptation to context modelling;
2. focusing on application driven advanced adaptive learning scenarios (such as no immediate feedback);
3. understanding and describing adaptation mechanisms in different settings, disciplines (such as philosophy) and applications.

• Handling Multiple Adaptive Elements in Predictive Modelling with Streaming Data (PhD co-supervisor) - funded by BU, 2011-2014
  
• INFER Computational Intelligence Platform for Evolving and Robust Predictive Systems (research task leader) - funded by EU FP7, 2010-2014
  
• CAPA Context Awareness in Predictive Analytics (researcher) - funded by STW (NWO), 2011-2015
  
• Food Sales Prediction (researcher)
  
• CFB Boilers Sensors Data Mining (researcher)
  

Professional Activities

Program Committee Member

Reviewer for conferences

Reviewer for journals

• Pattern Recognition, Elsevier (2009-2012)
  
• Computational Statistics and Data Analysis, Elsevier (2012)
• Knowledge Information Systems, Springer (2011)
  
• Information Sciences, Elsevier (2011-2012)
• Information Systems, Elsevier (2011-2012)
• Intelligent Systems in Accounting, Finance and Management, Wiley (2011)
• IEEE Transactions on Neural Networks (2010-2011)
• Advances in Data Analysis and Classification, Springer (2010)
• Journal of Pattern Recognition Research (2009-2010)
• Pattern Recognition Letters, Elsevier (2009)
• European Journal of Operational Research, Elsevier (2008-2009)
• Journal of Graphical and Computational Statistics, ASA (2008)

Workshop organizer

• 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

Tutorialist

Selected Talks

2012

• Adaptive learning from drifting data, University of Konstanz, Germany slides
  

2011

• 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

2010

• 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.

2009

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

2008

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

2007

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

Thesis Supervision