Papers

  • Mining Topological Structure in Graphs through Forest Representations
    Robin Vandaele, Yvan Saeys, and Tijl De Bie
    (to appear) In The Journal of Machine Learning Research (JMLR), 2020.
  • Graph Approximations to Geodesics on Metric Graphs
    Robin Vandaele, Yvan Saeys, and Tijl De Bie
    (to appear) In The International Conference on Pattern Recognition (ICPR), 2020.
  • The Boundary Coefficient: a Vertex Measure for Visualizing and Finding Structure in Weighted Graphs
    Robin Vandaele, Yvan Saeys, and Tijl De Bie
    In the KDD Workshop on Mining and Learning with Graphs (MLG), 2019.
    paper  
  • Local topological data analysis to uncover the global structure of data approaching graph-structured topologies
    Robin Vandaele, Tijl De Bie, and Yvan Saeys
    In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), 2018.
    paper  

Working Experience

  • Ph.D. Researcher, IDLab, Department of Electronics and Information Systems, Ghent University, 2016 - now.
  • Visiting Student Researcher, Stanford School of Medicine, Department of Medicine/Division of Biomedical Informatics Research, Stanford University, 2020, March - May.

Teaching

Community Services

Organisation of conferences, workshops, panels

  • ECML-PKDD Workshop on Applications of Topological Data Analysis (ATDA), 2019.

Reviewer for journals

  • Transactions on Knowledge Discovery from Data.

Program committee member for conferences and workshops

  • NeurIPS Workshop on Topological Data Analysis and Beyond (TDA & Beyond), 2020.
  • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery, 2019.
  • ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2018.

Last modified on