Papers

  • Stable Topological Signatures for Metric Trees through Graph Approximations
    Robin Vandaele, Bastian Rieck, Yvan Saeys, and Tijl De Bie
    (to appear) In Pattern Recognition Letters (PRL), 2021.
  • 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.
  • Topological image modification for object detection and topological image processing of skin lesions
    Robin Vandaele, Guillaume Adrien Nervo, and Olivier Gevaert
    In Nature Scientific Reports, 2020.
    paper  
  • Mining Topological Structure in Graphs through Forest Representations
    Robin Vandaele, Yvan Saeys, and Tijl De Bie
    In The Journal of Machine Learning Research (JMLR), 2020.
    paper  
  • 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  

Theses

  • Topological Inference in Graphs and Images
    Robin Vandaele, Yvan Saeys, and Tijl De Bie
    Doctoral dissertation submitted to obtain the academic degree of Doctor of Computer Science Engineering, Ghent University, 2020.
    thesis  
  • Topological Data Analysis of Metric Graphs for Evaluating Cell Trajectory Data Representations
    Robin Vandaele, Tijl De Bie, and Yvan Saeys
    Master dissertation submitted in order to obtain the academic degree of Master of Science in Statistical Data Analysis, Ghent University, 2020.
    thesis  
  • Reverse mathematics of the Browder-Göhde-Kirk fixed point theorem
    Robin Vandaele, Andreas Weiermann, and Paul Shafer
    Master dissertation submitted in order to obtain the academic degree of Master of Science in Mathematics, Ghent University, 2016.
    thesis  

Code & Tutorials

  • Backbone inference and topological data analysis of graphs (R).
  • Topological image modification and processing (Python).

Working Experience

  • Postdoctoral Researcher, Department of Applied Mathematics, Computer Science and Statistics, Ghent University, 2021 - now.
  • PhD Researcher, IDLab, Department of Electronics and Information Systems, Ghent University, 2016 - 2020.
  • Visiting Student Researcher, Stanford School of Medicine, Department of Medicine/Division of Biomedical Informatics Research, Stanford University, 2020, March - May.

Prizes & Awards

  • Quetelet Prize for best Master's thesis in Statistical Data Analysis within the field of biostatistics, 2020.

Education

  • PhD in Computer Science Engineering, 2020.
  • MSc in Statistical Data Analysis, Major Computational Statistics, 2020.
  • MSc in Mathematics, Major Pure Mathematics, Minor Research, 2016.
  • BSc in Mathematics, Minor Biology, 2015.

Teaching

Community Services

Organisation of conferences, workshops, panels

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

Reviewer for journals

  • Transactions on Neural Networks and Learning Systems.
  • Neurocomputing.
  • Transactions on Knowledge Discovery from Data.

Program committee member for conferences and workshops

  • ICLR Workshop on Geometrical and Topological Representation Learning (GTRL), 2021.
  • SIAM International Conference on Data Mining (SDM21), 2021.
  • NeurIPS Workshop on Topological Data Analysis and Beyond (TDA & Beyond), 2020.
  • European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD), 2019.
  • ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA), 2018.

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