Luana Ruiz

Assistant Professor, Department of Applied Mathematics and Statistics, Johns Hopkins University

Wyman Park Building N452

Baltimore, MD 21211

lrubini1-at-jh-dot-edu

I am an assistant professor with the Department of Applied Mathematics and Statistics at Johns Hopkins University, the Mathematical Institute for Data Science (MINDS), and the Data Science and Artificial Intelligence Institute (DSAI). Before that, I was a METEOR and FODSI postdoctoral fellow working with Prof. Stefanie Jegelka at MIT, and a Google Research Fellow at the Simons Institute for the Theory of Computing. I obtained my PhD from the Electrical and Systems Engineering Department at Penn, where I was very fortunate to be advised by Prof. Alejandro Ribeiro.

My primary research interests are in the areas of machine learning and signal processing over networks. My current work focuses on large-scale graph information processing and graph neural networks. Please check my CV here and a selected list of publications below.

news

May 11, 2024	In Vienna to present our spotlight paper “A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs” (with Thien Le and Stefanie Jegelka) at ICLR’24.
Apr 30, 2024	Our papers on manifold neural networks (with Zhiyang Wang and Alejandro Ribeiro) were accepted to the IEEE Trasactions in Signal Processing. Check them out below!
Apr 14, 2024	In Seoul to present our paper “A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs” (with Teresa Huang and Soledad Villar) at ICASSP’24.
Dec 9, 2023	Invited talk “Machine Learning on Large-Scale Graphs: Graphon NNs and Learning by Transference” at the Canadian Mathematical Society Winter Meeting.
Nov 16, 2023	Invited long talk “Large-Scale Graph Machine Learning: Tradeoffs, Guarantees and Dynamics” at DeepMath 2023.
Oct 17, 2023	New preprint A Local Graph Limits Perspective on Sampling-Based GNNs with Yeganeh and Amin.

selected publications

2024

Stability to Deformations of Manifold Filters and Manifold Neural Networks

Z. Wang, L. Ruiz, and A. Ribeiro

IEEE Trans. Signal Process., 2024

@article{wang2021stability,
  title = {Stability to Deformations of Manifold Filters and Manifold Neural Networks},
  author = {Wang, Z. and Ruiz, L. and Ribeiro, A.},
  journal = {IEEE Trans. Signal Process.},
  volume = {72},
  year = {2024},
  pages = {2130--2146},
  publisher = {IEEE},
}

Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs

Z. Wang, L. Ruiz, and A. Ribeiro

IEEE Trans. Signal Process., 2024

@article{wang2023convergence,
  title = {Geometric Graph Filters and Neural Networks: Limit Properties and Discriminability Trade-offs},
  author = {Wang, Z. and Ruiz, L. and Ribeiro, A.},
  journal = {IEEE Trans. Signal Process.},
  volume = {72},
  year = {2024},
  pages = {2244--2259},
  publisher = {IEEE},
}

A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs (Spotlight)

T. Le, L. Ruiz, and S. Jegelka

In 12th ICLR, 7–11 may 2024

@inproceedings{le24-poincare,
  title = {A Poincar\'e Inequality and Consistency Results for Signal Sampling on Large Graphs (Spotlight)},
  author = {Le, T. and Ruiz, L. and Jegelka, S.},
  booktitle = {12th ICLR},
  address = {Vienna, Austria},
  year = {2024},
  month = {7--11 May},
}

A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs

L. Ruiz, N. Huang, and S. Villar

In 49th ICASSP, 14-19 apr. 2024

@inproceedings{ruiz2024icassp,
  title = {A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs},
  author = {Ruiz, L. and Huang, N. and Villar, S.},
  booktitle = {49th ICASSP},
  address = {Seoul, South Korea},
  year = {2024},
  month = {14-19 Apr.},
}

2023

Learning by Transference: Training Graph Neural Networks on Growing Graphs

J. Cervino, L. Ruiz, and A. Ribeiro

IEEE Trans. Signal Process., 14-19 apr. 2023

@article{cervino2021increase,
  title = {Learning by Transference: Training Graph Neural Networks on Growing Graphs},
  author = {Cervino, J. and Ruiz, L. and Ribeiro, A.},
  journal = {IEEE Trans. Signal Process.},
  volume = {71},
  pages = {233--247},
  year = {2023},
  publisher = {IEEE},
}

Transferability Properties of Graph Neural Networks

L. Ruiz, L. F. O. Chamon, and A. Ribeiro

IEEE Trans. Signal Process., 14-19 apr. 2023

@article{ruiz2021transferability,
  title = {Transferability Properties of Graph Neural Networks},
  author = {Ruiz, L. and Chamon, L. F. O. and Ribeiro, A.},
  journal = {IEEE Trans. Signal Process.},
  volume = {71},
  year = {2023},
  pages = {3473--3489},
  publisher = {IEEE},
}

Graph Neural Tangent Kernel: Convergence on Large Graphs

S. Krishnagopal, and L. Ruiz

In 40th ICML, 23-29 jul. 2023

@inproceedings{krishnagopal23-gntk,
  title = {Graph Neural Tangent Kernel: Convergence on Large Graphs},
  author = {Krishnagopal, S. and Ruiz, L.},
  booktitle = {40th ICML},
  address = {Honolulu, HI},
  year = {2023},
  month = {23-29 Jul.},
}

2021

Graph Neural Networks: Architectures, Stability and Transferability

L. Ruiz, F. Gama, and A. Ribeiro

Proc. IEEE, 23-29 jul. 2021

@article{ruiz2020gnns,
  title = {Graph Neural Networks: Architectures, Stability and Transferability},
  author = {Ruiz, L. and Gama, F. and Ribeiro, A.},
  journal = {Proc. IEEE},
  volume = {109},
  number = {5},
  pages = {660--682},
  year = {2021},
  publisher = {IEEE},
}

Graphon Signal Processing

L. Ruiz, L. F. O. Chamon, and A. Ribeiro

Trans. Signal Process., 23-29 jul. 2021

@article{ruiz2020graphonsp,
  title = {Graphon Signal Processing},
  author = {Ruiz, L. and Chamon, L. F. O. and Ribeiro, A.},
  journal = {Trans. Signal Process.},
  volume = {69},
  pages = {4961--4976},
  year = {2021},
  publisher = {IEEE},
}

Stability of Neural Networks on Riemannian Manifolds (Best Paper Award)

Z. Wang, L. Ruiz, and A. Ribeiro

In 29th EUSIPCO, 23-27 aug. 2021

@inproceedings{wang2021manifold,
  title = {Stability of Neural Networks on {R}iemannian Manifolds (Best Paper Award)},
  author = {Wang, Z. and Ruiz, L. and Ribeiro, A.},
  booktitle = {29th EUSIPCO},
  address = {Dublin, Ireland (Virtual)},
  year = {2021},
  month = {23-27 Aug.},
  publisher = {IEEE},
}

Iterative Decoding for Compositional Generalization in Transformers

L. Ruiz, J. Ainslie, and S. Ontañón

arXiv:2110.04169 [cs.LG], 23-27 aug. 2021

@article{ruiz2021iterative,
  title = {Iterative Decoding for Compositional Generalization in Transformers},
  author = {Ruiz, L. and Ainslie, J. and Onta{\~n}{\'o}n, S.},
  journal = {arXiv:2110.04169 [cs.LG]},
  year = {2021},
}

2020

Gated Graph Recurrent Neural Networks

L. Ruiz, F. Gama, and A. Ribeiro

Trans. Signal Process., 23-27 aug. 2020

@article{ruiz2020grnns,
  author = {Ruiz, L. and Gama, F. and Ribeiro, A.},
  journal = {Trans. Signal Process.},
  title = {Gated Graph Recurrent Neural Networks},
  volume = {68},
  pages = {6303--6318},
  year = {2020},
  publisher = {IEEE},
}

The Graphon Fourier Transform

L. Ruiz, L. F. O. Chamon, and A. Ribeiro

In 45th ICASSP, 4-8 may 2020

@inproceedings{ruiz2019graphon,
  title = {The {G}raphon {F}ourier {T}ransform},
  author = {Ruiz, L. and Chamon, L. F. O. and Ribeiro, A.},
  booktitle = {45th ICASSP},
  pages = {5660-5664},
  address = {Barcelona, Spain (Virtual)},
  year = {2020},
  month = {4-8 May},
  organization = {IEEE},
}

Graphon Neural Networks and the Transferability of Graph Neural Networks

L. Ruiz, L. F. O. Chamon, and A. Ribeiro

In 34th NeurIPS, 6-12 dec. 2020

@inproceedings{ruiz20-transf,
  title = {Graphon Neural Networks and the Transferability of Graph Neural Networks},
  author = {Ruiz, L. and Chamon, L. F. O. and Ribeiro, A.},
  booktitle = {34th NeurIPS},
  address = {Vancouver, BC (Virtual)},
  year = {2020},
  month = {6-12 Dec.},
  publisher = {NeurIPS Foundation},
}

2019

Gated Graph Convolutional Recurrent Neural Networks (Best Paper Award)

L. Ruiz, F. Gama, and A. Ribeiro

In 27th EUSIPCO, 2-6 sep. 2019

@inproceedings{ruiz18-grnns,
  title = {Gated Graph Convolutional Recurrent Neural Networks (Best Paper Award)},
  author = {Ruiz, L. and Gama, F. and Ribeiro, A.},
  booktitle = {27th EUSIPCO},
  pages = {1-5},
  address = {A Coruna, Spain},
  year = {2019},
  month = {2-6 Sep.},
  organization = {EURASIP},
}