About me

Since March 2011 I am a lecturer in Computational Intelligence at Bournemouth University, UK and
a research task leader on advanced modeling and adaptive learning in the INFER.eu project.
Prior to that I was a postdoctoral researcher at Eindhoven University of Technology, the Netherlands.
I obtained my PhD from Vilnius University, Lithuania in April 2010.

Research Interests

adaptive online learning, evolving data streams
handling concept drift and hidden contexts
change detection and change management
context aware learning
predictive analytics applications

My research in adaptive learning falls into three main tracks:

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

Publications

list and pre-prints

Projects

I am involved in these projects and industrial collaborations:

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

ECMLPKDD'12, FSKD'12, HAIS'12, ICPRAM'12, MCDS'12@ADBIS, MMAML'12@ACIIDS, PROMAMEDS'12@CBMS,

CIDUE'11, ECMLPKDD'11, FSKD'11, HAIS'11, IJCAI'11, ISDA'11, SAC'11-Data Streams,
CBMS'10, FSKD'10, IVUS'10

Reviewer for conferences

IJCNN'12,
IJCNN'11,
ECML/PKDD'10, EDM'10, IJCNN'10, AAAI'10,
BNAIC'09, ECMLPKDD'09

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)
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 HaCDAIS'11 workshop
Co-organizer of INFER-APS'11 workshop
Co-Chair of HaCDAIS'10 workshop
Co-organizer of DHDHD'10 workshop

Tutorialist

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

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.