Christopher Morris

Otto-Hahn-Straße 14

I am a PhD student at TU Dortmund University advised by Petra Mutzel. I also frequently collaborated with Kristian Kersting. My PhD research is 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 my CV.

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

Conference Papers

  • Deep Graph Matching Consensus
    Matthias Fey, Jan E. Lenssen, Christopher Morris, Jonathan Masci, Nils M. Kriege.
    International Conference on Learning Representations (ICLR) 2020.
    Temporal Graph Kernels for Classifying Dissemination Processes (Preprint arXiv:1911.05496)
    Lutz Oettershagen, Nils Kriege, Christopher Morris, Petra Mutzel.
    SIAM International Conference on Data Mining (SDM) 2020.

Journal Papers

  • A Survey on Graph Kernels (Preprint arXiv:1903.11835)
    Nils M. Kriege, Fredrik D. Johansson, Christopher Morris,
    Applied Network Science, Machine learning with graphs, 2019, accepted for publication.

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.