Papers

  • Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information
    Bo Kang, Darío García García, Jefrey Lijffijt, Raúl Santos-Rodríguez, and Tijl De Bie
    arXiv, 2019.
    preprint
  • ExplaiNE: An Approach for Explaining Network Embedding-based Link Predictions
    Bo Kang, Jefrey Lijffijt, and Tijl De Bie
    arXiv, 2019.
    preprint
  • A constrained randomization approach to interactive visual data exploration with subjective feedback
    Bo Kang, Kai Puolamäki, Jefrey Lijffijt, and Tijl De Bie
    In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.
    paper
  • Conditional Network Embeddings
    Bo Kang, Jefrey Lijffijt, and Tijl De Bie
    In International Conference on Learning Representations (ICLR), 2019.
    paper
  • Subjectively Interesting Motifs in Time Series
    Junning Deng, Jefrey Lijffijt, Bo Kang and Tijl De Bie
    In 3rd ECML-PKDD Workshop on Advanced Analytics and Learning on Temporal Data (ECML-PKDD), 2018.
    paper
  • SICA: Subjectively Interesting Component Analysis
    Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, and Tijl De Bie
    In Data Mining and Knowledge Discovery (DAMI), 2018.
    paper
  • Subjectively interesting subgroup discovery on real-valued targets
    Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, and Tijl De Bie
    In IEEE International Conference on Data Engineering (ICDE), 2018.
    preprint   extended version at arXiv
  • Interactive Visual Data Exploration with Subjective Feedback: An Information-Theoretic Approach
    Kai Puolamäki, Emilia Oikarinen, Bo Kang, Jefrey Lijffijt, and Tijl De Bie
    In IEEE International Conference on Data Engineering (ICDE), 2018.
    preprint   extended version at arXiv
  • Clipped Projections for More Informative Visualizations [A Work-in-Progress Report]
    Bo Kang, Junning Deng, Jefrey Lijffijt, and Tijl De Bie
    In ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2017.
    paper   poster
  • Interactive Visual Data Exploration with Subjective Feedback
    Kai Puolamäki, Bo Kang, Jefrey Lijffijt, and Tijl De Bie
    In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2016.
    paper
  • A Tool for Subjective and Interactive Visual Data Exploration
    Bo Kang, Kai Puolamäki, Jefrey Lijffijt, and Tijl De Bie
    In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2016.
    paper   demo
  • Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations
    Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodríguez, and Tijl De Bie
    In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016.
    paper   poster   video
  • SIDE: A Web App for Interactive Visual Data Exploration with Subjective Feedback
    Jefrey Lijffijt, Bo Kang, Kai Puolamäki, and Tijl De Bie
    In ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2016.
    paper
  • Informative Data Projections: A Framework and Two Examples
    Tijl De Bie, Jefrey Lijffijt, Raúl Santos-Rodríguez, and Bo Kang
    In European Symposium on Artificial Neural Networks (ESANN), 2016.
    preprint
  • P-N-RMiner: A Generic Framework for Mining Interesting Structured Relational Patterns
    Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, and Tijl De Bie
    In International Journal of Data Science and Analytics, 2016.
    paper
  • P-N-RMiner: A Generic Framework for Mining Interesting Structured Relational Patterns
    Jefrey Lijffijt, Eirini Spyropoulou, Bo Kang, and Tijl De Bie
    In IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2015.
    paper
  • Creedo―Scalable and Repeatable Extrinsic Evaluation for Pattern Discovery Systems by Online User Studies
    Mario Boley, Maike Krause-Traudes, Bo Kang, and Björn Jacobs
    In ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2015.
    paper   project
  • One Click Mining―Interactive Local Pattern Discovery through Implicit Preference and Performance Learning
    Mario Boley, Michael Mampaey, Bo Kang, Pavel Tokmakov, and Stefan Wrobel
    In ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2013.
    paper   project

Software

  • Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information   project
  • DataUntangler: Interactive Data Exploration with Embeddings and Probing   project
  • CNE: Conditional Network Embeddings   project
  • SIDE: A Tool for Subjective and Interactive Visual Data Exploration   demo
  • SICA: Subjectively Interesting Component Analysis   code

Working Experience

  • Research Staff, Ghent University, 2015 - now.
  • Research Intern, Facebook AI, Jun.2018 - Oct.2018.
  • Research Staff, University of Bristol, Summer 2015.
  • Research Assistant, Fraunhofer IAIS, 2012 - 2015.
  • Research Assistant, University of Bonn, Winter 2012.

Teaching

Talks and Posters

  • Conditional t-SNE
    Tufts University, United States, 2018.
    talk slides (tba)
  • CLIPPR: Maximally Informative CLIPped PRojections with Bounding Regions
    with Dylan Cashman, Remco Chang, Jefrey Lijffijt and Tijl De Bie
    In IEEE Visual Analytics in Science and Technology (VAST), 2018.
    poster   abstract
  • A graph based approach for formalizing subjective interestingness of data projections
    with Jefrey Lijffijt, Raúl Santos-Rodríguez and Tijl De Bie
    In International Symposium on Intelligent Data Analysis (IDA), 2015.
    poster
  • One Click Mining: Interactive Local Pattern Discovery through Implicit Preference and Performance Learning
    Advanced Database Research and Modeling Group, University of Antwerp, Belgium, 2013.
    talk slides

Community Services

Organisation of conferences, workshops

  • Web chair. European Conference of Machine Learning and Principles and Practices of Knowledge Discovery in Databases (ECML-PKDD 2020), Ghent, Belgium. Website
  • Co-chair. ECML-PKDD Workshop on Graph Embedding and Mining (GEM 2019), Würzburg, Germany. Website

Reviewer for journals

  • Machine Learning Journal (MLJ)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)

Program committee member for conferences and workshops

  • European Conference of Machine Learning and Principles and Practices of Knowledge Discovery in Databases (ECML-PKDD), 2016, 2017, 2018, 2019.
  • ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2017, 2018.
  • International Conference on Discovery Science (DS), 2018.
  • Computer Science Conference for University of Bonn Students (CSCUBS), 2014, 2015.

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