Nature Communications
Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis
A. F. Marcús, R. Jankowski, M. V. Miñana, C. Casacuberta, M. À. Serrano
Robert Jankowski
Postdoctoral Fellow at TU Delft.
I work with Maksim Kitsak on shortest paths in large incomplete networks. I received my PhD in network geometry from the University of Barcelona, where I studied network embeddings in multidimensional hyperbolic spaces with Marián Boguñá and M. Ángeles Serrano.
News
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Jun. 2026
Article: Trade-offs between structural richness and perceptual robustness in music network representations accepted in Physical Review Research.
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Jun. 2026
Article: HypBench: Hyperbolic Benchmark for Graph Neural Network Performance published in IEEE Transactions on Neural Networks and Learning Systems.
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Jun. 2026
Best Contributed Talk at the Network Science Informs AI Satellite at NetSci 2026.
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May. 2026
Article: Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis published in Nature Communications.
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Apr. 2026
New preprint: "Motif-based filtrations for persistent homology: A framework for graph isomorphism and property prediction" is available online.
Selected Publications
MLST
Task complexity shapes internal representations and robustness in neural networks
R. Jankowski, F. Radicchi, M. À. Serrano, M. Boguñá, S. Fortunato
Communications Physics
Mapping bipartite networks into multidimensional hyperbolic spaces
R. Jankowski, R. Aliakbarisani, M. À. Serrano, M. Boguñá
Nature Communications
The D-Mercator method for the multidimensional hyperbolic embedding of real networks
R. Jankowski, A. Allard, M. Boguñá, M. À. Serrano
Prospective Collaborators and Students
I am open to collaborations with researchers and students interested in network geometry, graph machine learning, and network science of neural networks.If you are interested in working together on these topics, feel free to contact me: research@robertjankowski.net.