Christopher Morris


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Université de Montréal Campus André-Aisenstadt Building 2920, Chemin de la Tour

I am postdoc at Polytechnique Montréal in the group of Andrea Lodi. Previously, I was a PhD student at TU Dortmund University advised by Petra Mutzel and Kristian Kersting. My PhD research was generously supported by the German Research Foundation, through the Collaborative Research Center SFB 876 -- Providing Information by Resource-Constrained Data Analysis, Project A6.

I develop machine learning methods for graphs, network, and relational data.

My research combines techniques from machine learning, graph algorithms, and CS theory, and revolves around the following questions:

  1. How do we effectively capture the structure of graphs and networks in a data-driven manner?
  2. How can we scale up such methods for large-scale data?
  3. How can such methods make combinatorial algorithms faster in a data-driven manner?

For more details, please refer to my CV.

Fun Fact: My Erdős number is at most 3 (via Petra Mutzel → Bojan Mohar → P. Erdős)

Conference Papers

  • Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings (Preprint arXiv:XXXX:XXXX)
    Christopher Morris, Gaurav Rattan, Petra Mutzel,
    Neural Information Processing Systems (NeurIPS) 2020.

Journal Papers

Workshop Papers

Preprints and Working Papers

  • Towards a practical $k$-dimensional Weisfeiler-Leman algorithm (Preprint arXiv:1904.01543)
    Christopher Morris, Petra Mutzel.


  • 15.01.2018–31.03.2018: Research stay at Stanford University with Jure Leskovec
I maintain a growing collection of benchmark datasets for supervised graph classification.