Invited
Talks, Tutorials, Panels, Paper and Poster Presentations
2017
(upcoming) Fairness,
Accountability and Transparency in Learning Analytics, Big Data-Driven Education Reform, Qufu Normal University (QFNU), China (November 2017)
(upcoming) FAT Analytics: facets of (un)fairness and (non)transparency, Responsible Data Science Seminar Series, VU Amsterdam (October 2017)
(upcoming) Responsible Predictive Analytics: facets of (un)fairness and (non)transparency Duisburg, Germany (October 2017)
Responsible Predictive Analytics, Inaugural Lecture, TU/e (September 2017)
BLPA: Bayesian
learn-predict-adjust method for online detection of recurrent change points,
IJCNN 2017, Anchorage, USA (May 2017)
Responsible Predictive
Analytics, University at Buffalo, NY, USA (May 2017)
Responsible Predictive
Analytics, JADS Seminar, Den Bosch, the Netherlands (April
2017)
Responsible Learning Analytics,
Berlin, Germany (April 2017)
Predictive Analytics for
Responsible Data Science, Lviv, Ukraine (March
2017)
Educational Data Mining and
Learning Analytics: A View from the Trenches, University of Waikato,
New Zealand (February 2017)
Predictive Analytics for
Responsible Data Science, Connected Intelligence Centre, UTS,
Sydney, Australia (February 2017)
Predictive Analytics on
Evolving Data Streams, Connected Intelligence Centre, UTS, Sydney,
Australia (February 2017)
Predictive Analytics for
Responsible Data Science, Data Analytics Centre, Department of
Finance, Services and Innovation, NSW government, Sydney, Australia (February
2017)
2016
Explaining soccer match outcomes with goal scoring opportunities predictive analytics, MLSA@ECMLPKDD’2016 (September 2016)
Application of Horizontal
Visibility Graph as a Robust Measure of Neurophysiological Signals Synchrony, IEEE
CBMS 2016 Belfast, Northern Ireland (June
2016)
Towards Responsible Predictive
Analytics, Invited talk at IBM Ireland Research Lab,
Dublin, Ireland (May 2016)
Predictive Analytics that
Works!?, Invited talk at the
Workshop on Data Mining for Medicine and Healthcare (DMMH@SDM’16), Miami,
USA (May 2016)
Modelling Recurrent Events for
Improving Online Change Detection, SIAM Data Mining (SDM’16), Miami, USA (May 2016)
Predictive Analytics that
Works!?, Invited seminar talk
at the School of Computing Science and Digital Media, Robert Gordon University,
Aberdeen, UK (April 2016)
On structure preserving sampling and approximate partitioning of graphs, ACM SAC’16, Pisa, Italy (April 2016)
2015
Ethics-awareness and
Accountability in Predictive Analytics, Invited seminar talk at the Institute for Adaptive and Neural
Computation, University of Edinburgh, UK
(November 2015)
Grand Challenges in Predictive Analytics, Invited talk at AI Ukraine 2015, Kharkov (September 2015)
Data-Driven Education and
Ethics-Aware Learning Analytics, Invited
talk at Big Data: Educational Analytics Research Methods workshop, University
of Tampere, Finland (August 2015)
Predictive Analytics on
Evolving Data Streams: Anticipating and Adapting to Changes in Known and Unknown
Contexts, Invited talk at HPCS
2015 Data mining track, Amsterdam
(July 2015)
Fairness, Accountability, and
Transparency in Machine Learning ICML
2015 Workshop Panel, Lille, France (July 2015)
Grand Challenges in Educational
Data Mining, Invited talk at
Machine Learning for Education ICML 2015 Workshop, Lille, France (July 2015)
Grand Challenges in Predictive
Analytics for EDM, Grand
Challenges in EDM and Related Research Areas Panel at EDM 2015, Madrid,
Spain (June 2015)
Ethics-aware Educational Data Mining, Privacy and Ethics in EDM Panel at EDM 2015, Madrid, Spain (June 2015)
2014
Ethics-aware Learning
Analytics, IRB and Big Data NSF Workshop, George Masson University,
USA (November
2014)
Predictive Analytics for Data-Driven
Education: Knowledge Discovery and Process Mining Perspectives, SIAT, Simon Fraser University, Canada (August 2014)
Putting Tweets on Plutchik’s Wheel: Rule-based Sentiment and Emotion Detection on Social Media, AICML, University of Alberta, Edmonton, Canada (July 2014)
Multi-modal Affective Data Analytics, AI Seminar, Department of Computing Science, University of Alberta, Edmonton, Canada (July 2014)
Context Aware Predictive
Analytics for Web Personalization,
Facebook, Menlo Park. CA (July 2014)
Data Analytics and Learning
MOOC: Voices From The
Field, 2nd Learning
Analytics Summer Institutes (LASI 2014), Harvard Graduate School of
Education, Cambridge, MA (July 2014)
Learning to Teach Like a
Bandit. Poster at Educational
Data Mining (EDM 2014), London, UK
(July 2014)
Changing the Face of Predictive
Analytics for Data-Driven Education. Invited talk at Search Labs, Microsoft Research, Mountain View, CA,
USA (June 2014)
From A/B Testing to
Personalization with Uplift Predictors. MOOCLets seminar talk, Barnum Center, Stanford University, CA, USA (June 2014)
Potential, Dangers and Next
Challenges in Educational Data Mining and Learning Analytics. Learning Analytics Seminar talk,
Teachers College, University of Columbia, NYC, USA (May 2014)
Context Discovery & Context
Integration in Predictive Web Analytics. Stern School of Business, New York University, NYC, USA (May 2014)
Predictive Analytics under
Concept Drift. Guest lecture
at the Faculty of Information Technology, University of Jyväskylä,
Finland
(April 2014)
Theory and Practice of Handling
Concept Drift in Predictive Analytics. Invited talk at Knowledge
Discovery and Intelligent Systems research group, University of Cordoba (January 2014)
State-of-the-art, Recent Trends
and Next Challenges in Concept Drift Research. Invited talk at the Colloquium series on Machine Learning, Pattern
Recognition, and Computer Vision, TU Delft (January 2014)
2013
Getting
Ready for Change: Handling Concept Drift in Predictive Analytics.
Invited talk at Microsoft Research
Redmond, WA, USA (December 2013)
Context-Aware Predictive Web Analytics. Lunch talk at CLUES, Microsoft Research Redmond, WA, USA (December 2013)
Predicting Current User Intent
with Contextual Markov Models. Domain
Driven Data Mining, DDDM@ICDM’2013, Dallas, USA (December
2013)
Context-Aware Predictive Analytics. Data Science Center Eindhoven (DSC/e) Launch Symposium, TU Eindhoven (December 2013)
Microblogging Social Networks:
Applications and Analysis. Data
Science Center Eindhoven (DSC/e) Launch Symposium, TU Eindhoven (December 2013)
Making Affective Data Analytics
Accessible for All. Invited
talk at Machine Learning Summer School “Learning with Big Data”, Hammamet, Tunisia (September
2013)
Computational Advertising. Tutorial at Machine Learning Summer School “Learning
with Big Data”, Hammamet,
Tunisia (September 2013)
Cross-lingual Polarity Detection with Machine Translation, Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM@KDD2013), Chicago, USA (August 2013)
Predictive Web Analytics. Invited talk at Healthcare Information
Management forum, Philips Research, Eindhoven, the Netherlands (July 2013)
Predictive Web Analytics. All
models are wrong, but which ones are useful? Invited talk at LIAAD, University of Porto, Portugal (June 2013)
Stress Detection from Speech
and Galvanic Skin Response Signals. The 26th IEEE Symposium on Computer Based
Medical Systems (IEEE CBMS’2013), Porto, Portugal (June 2013)
Predictive Analytics: Insights
on Internals and Pitfalls to Avoid. Invited talk at the Next Generation Data Analytics Workshop, Amsterdam,
the Netherlands (June 2013)
Modeling Intents of Web Site
Visitors. Invited talk at HIIT seminar, Aalto University,
Helsinki, Finland (June 2013)
Getting Ready for Change: Towards More Accurate, Reactive &
Proactive Predictive Analytics. Public
lecture at the Faculty of Information Technology, University of Jyväskylä, Finland (May 2013)
2012
Engineering Sentiment Analytics with Multimodal
Affective Data. Invited
talk at the First International
Workshop on Sentiment Discovery from Affective Data (SDAD 2012 @ ECMLPKDD2012),
Bristol, UK (September 2012)
Engineering Stress Analytics:
Towards Intelligent Analysis of Multimodal Affective Data. Information Systems colloquium (IE&IS/IS -
W&I/IS), TU/e, Eindhoven (July
2012)
Advanced Topics
in Data Stream Mining. ECMLPKDD
2012 tutorial, Bristol, UK (September
2012)
Engineering Context Aware
Predictive Analytics: Motivation, Potential, Challenges. University
of San Cristóbal de La Laguna, Tenerife, Spain (May 2012)
Stess@Work: from measuring stress to its understanding, prediction
and handling with personalized coaching. ACM International Health Informatics Symposium (IHI 2012), Miami,
USA (January 2012)
2011
What's your current stress level?
Detection of stress patterns from GSR sensor data. (HaCDAIS @
ICDM’2011) Vancouver, Canada
(December 2011)
SentiCorr:
Multilingual Sentiment Analysis of Personal Correspondence. (Demo @ ICDM’2011) Vancouver, Canada (December 2011)
Stress@work: From Stress Measurement to Understanding the
Stressors. University of Portsmouth, UK (November 2011)
Context
Aware Predictive Analytics: Motivation, Potential, Challenges. University
of Bournemouth, UK (October 2011)
Context-aware personal route recognition.
The 14th International
Conference on Discovery Science (DS 2011), Porto, Portugal (October
2011)
Handling Concept Drift: Importance, Challenges and Solutions. Tutorial at the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2011), Shenzhen, China (May 2011)
Educational Data Mining
& Learning Analytics for All: Potential, Dangers, Challenge. Learning
Analytics Seminar, Utrecht, the Netherlands (August 2011)
2010
Learning with Actionable
Attributes: Learning to Effectively Help Those Who Need Help. University of Sydney, Australia
(December 2010)
Heart Failure Hospitalization Prediction in
Remote Patient Management Systems. The
24th IEEE Symposium on
Computer Based Medical Systems (IEEE CBMS’2010), Perth, Australia (October 2010)
Handling
Concept Drift in Medical Applications: Importance, Challenges and Solutions. Tutorial at the 24th IEEE Symposium on Computer Based Medical Systems
(IEEE CBMS’2010), Perth, Australia (October
2010)
Dealing
with Concept Drift in Adaptive Information Systems. “Learning
from Evolving Data” tutorial block at
ECML/PKDD 2010, Barcelona,
Spain, (September 2010)
Handling Concept Drift: An
Application Perspective. DHDHD 2010 Workshop, TU/e, Eindhoven (September 2010)
Towards EDM framework for Personalization
of Information Services in RPM Systems (poster) The 3rd International Conference on Educational Data Mining (EDM’2010),
Pittsburg, USA (July 2010)
2009
Context-aware prediction in the
wild: lessons learnt from case studies. Information Systems colloquium
(IE&IS/IS - W&I/IS), TU/e,
Eindhoven (October 2009)
OMFP: An Approach for Online
Mass Flow Prediction in CFB Boilers. The 12th International Conference on
Discovery Science (DS’09), Porto,
Portugal (October 2009)
Process Mining the
Student Assessment Data. (poster) The 2nd International
Conference on Educational Data Mining (EDM’09), Cordoba, Spain (July 2009)
Online Mass Flow Prediction in
CFB Boilers. The
9th Industrial Conference on Data Mining (ICDM’09), Leipzig, Germany (July 2009)
Handling
Outliers and Concept Drift in Online Mass Flow Prediction in CFB Boilers. The 3rd International Workshop on Knowledge
Discovery from Sensor Data (SensorKDD-2009), Paris, France (June
2009)
Food Sales Prediction: “If Only It Knew What We Know”. The 2nd International Workshop on Domain Driven Data Mining (DDDM’08 at IEEE ICDM 2008), Pisa, Italy (December 2009)
2008
Educational Data Mining, Full day tutorial at Open University,
Heerlen, the Netherlands, (December 2008)
The Cross-Roads of Data Mining,
Adaptive Systems and E-Learning. Philips
High Tech Campus, Eindhoven,
the Netherlands (August 2008)
Mining the Student Assessment
Data: Lessons Drawn from a Small Scale Case Study. (poster) The 1st
International Conference on
Educational Data Mining (EDM’08), Montreal, Canada (June 2008)
Effectiveness of Local Feature
Selection in Ensemble Learning for Prediction of Antimicrobial Resistance. The 21st
IEEE Symposium on Computer Based Medical Systems (IEEE CBMS’08, Data Mining
Track), Jyväskylä, Finland (June 2008)
Educational Data Mining
Frontiers. Education Day (Faculty of Electrical Engineering, TU/e), Turnhout,
Belgium (May 2008)
MDL Principle in Process Models Evaluation. Spring Workshop on Mining and Learning (SML’08), Traben-Trarbach, Germany (April 2008)
2007
Facets of Concept Drift Problem
in Adaptive Information Systems. LIAAD/LIACC
Seminar, University of Porto, Portugal (October 2007)
A
Framework for Guiding the Museum Tour Personalization. Personalization
Enhanced Access to Cultural Heritage (PATCH’07) Workshop at UM’2007, Corfu,
Greece
Handling Concept Drift in
Adaptive Information Systems. The
GOOD-dag 2007, Hingene, Bornem,
Belgium
2006
Random Forest with Dynamic
Integration of Trees. (poster) The 17th European Conf. on Machine Learning
(ECML/PKDD'06), Berlin,
Germany
Towards Better Understanding of
Circulating Fluidized Bed Boilers: a Data Mining Approach. (poster) The 2nd Workshop on Practical Data
Mining: Applications, Experiences and ChallengesDMBiz’06 (ECML/PKDD’06), Berlin,
Germany
Dynamic
Integration of Classifiers for Handling Concept Drift. The 19th
IEEE Symposium on Computer Based Medial Systems (IEEE CBMS’06, Data Mining
Track), Salt Lake City, Utah, USA 2006
Class Noise and
Supervised Learning in Medical Domains: The Effect of Feature Extraction. The 19st
IEEE Symposium on Computer Based Medial Systems (IEEE CBMS’06, Data Mining
Track), Salt Lake City, Utah, USA 2006
The
Impact of Sample Reduction on PCA-based Feature Extraction for Supervised
Learning. The 21st ACM Symposium on Applied
Computing (ACM SAC’06, Data Mining Track), Dijon, France, 2006
2002-2005
Feature Extraction for
Supervised Learning in Knowledge Discovery Systems. PhD thesis public examination, Agora, Aud. 2,
JYU, Jyväskylä, 12:00, December 20, 2005
Why Data Mining Does
Not Contribute to Business? Data Mining for Business Workshop
(DMBiz) as part of the 16th European Conference
on Machine Learning (ECML) and the 9th European Conference on Principles and
Practice of Knowledge Discovery in Databases (PKDD), and Porto, Portugal,
2005
On Combining
Principal Components with Parametric LDA-based Feature Extraction for
Supervised Learning. ADBIS
Workshop on Data Mining and Knowledge Discovery, Tallinn, Estonia, 2005
Competitive advantage
from Data Mining: Lessons learnt in the Information Systems field. (Invited
paper) Int. DEXA’05 Workshop on Philosophies and Methodologies for
Knowledge Discovery PMKD’05, Copenhagen, Denmark, 2005
Knowledge Management
Challenges in Knowledge Discovery Systems. Int. DEXA’05
Workshop on Theory and Applications of Knowledge Management TAKMA’05,
Copenhagen, Denmark, 2005
Sequential Genetic Search for Ensemble Feature Selection. The 19th International Joint Conference on Artificial Intelligence IJCAI-05, Edinburgh, UK, 2005
Local Dimensionality Reduction
within Natural Clusters for Medical Data Analysis. The 18th IEEE Int. Symposium on
Computer-Based Medical Systems CBMS 2005, Dublin, Ireland, 2005
The Impact of Feature Extraction on the Performance of a Classifier: kNN, Na‹ve Bayes and C4.5. The 18th CSCSI Conference on Artificial Intelligence AI’05, Victoria, Canada, 2005
Knowledge Discovery from Microbiology Data: Many-sided Analysis of Antibiotic Resistance in Nosocomial Infections. The 3rd Conference Professional Knowledge Management, Current Aspects of Knowledge Management in Medicine Workshop KMM’05, Kaiserslautern, Germany, 2005
Data Mining Strategy Selection
via Empirical and Constructive Induction.
The 23rd International Conference on Applied Informatics, Innsbruck,
Austria, 2005
The Iterative and Interactive Data Mining Process: The Information Systems Development and Knowledge Management Perspectives. The 4th IEEE Int. Conf on Data Mining ICDM’04, 3rd Foundation of Data Mining Workshop, Brighton, UK, 2004
On the Use of Information
Systems Research Methods in Data Mining.
The 13th Int. Conf. On Information Systems Development, Vilnius,
Lithuania, 2004
Meta-Knowledge
Management in Multistrategy
Process-Oriented Knowledge Discovery Systems. The 13th Int. Conf. On Information
Systems Development, Vilnius, Lithuania, 2004
Feature Extraction for
Classification in Knowledge Discovery Systems. The 7th Int.
Conf. on Knowledge-Based Intelligent Information & Engineering
Systems KES’03, University of Oxford,
United Kingdom, 2003
Feature Extraction for
Classification in the Data Mining Process. The 10th Int. Conf. Knowledge-Dialogue-Solution
KDS’03, Varna, Bulgaria, 2003
PCA-based Feature Extraction
for Classification. Northern Ireland
Knowledge Engineering Laboratory, University of Ulster, Belfast, Northern Ireland, UK, 2002