Beatrice Bevilacqua

ML Research Scientist, Arc Institute

bbevilac [AT] purdue.edu

Bio

Hi! I am an ML Research Scientist at the Arc Institute, where I build foundation models for perturbation prediction in single-cell biology. I obtained my Ph.D. in Computer Science at Purdue University, advised by Prof. Bruno Ribeiro, and in close collaboration with Prof. Haggai Maron. My research focuses on foundation models for structured data, with an emphasis on invariances to improve generalization on real-world biological data.

Publications

Most recent publications on Google Scholar. ‡ indicates equal contribution.

Predicting cellular responses to perturbation across diverse contexts with State

Abhinav K. Adduri, Dhruv Gautam, Beatrice Bevilacqua, Alishba Imran, Rohan Shah, Mohsen Naghipourfar, Noam Teyssier, Rajesh Ilango, Sanjay Nagaraj, Mingze Dong, Chiara Ricci-Tam, Christopher Carpenter, Vishvak Subramanyam, Aidan Winters, Sravya Tirukkovular, Jeremy Sullivan, Brian S. Plosky, Basak Eraslan, Nicholas D. Youngblut, Jure Leskovec, Luke A. Gilbert, Silvana Konermann, Patrick D. Hsu, Alexander Dobin, Dave P. Burke, Hani Goodarzi, Yusuf H. Roohani

bioRxiv 2025

Paper

Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings

Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec, Bruno Ribeiro

ICLR 2025

Paper Code

Granola: Adaptive Normalization for Graph Neural Networks

Moshe Eliasof‡, Beatrice Bevilacqua‡, Carola-Bibiane Schönlieb, Haggai Maron

NeurIPS 2024

Paper

Efficient Subgraph GNNs by Learning Effective Selection Policies

Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

ICLR 2024

Paper Code

Neural Algorithmic Reasoning with Causal Regularisation

Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Veličković

ICML 2023

Paper

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Fabrizio Frasca‡, Beatrice Bevilacqua‡, Michael M. Bronstein, Haggai Maron

NeurIPS 2022, Oral (199 / 10,411 submissions)

Paper Code

Equivariant Subgraph Aggregation Networks

Beatrice Bevilacqua‡, Fabrizio Frasca‡, Derek Lim‡, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

ICLR 2022, Spotlight (174 / 3391 submissions)

Paper Video Code

Size-Invariant Graph Representations for Graph Classification Extrapolations

Beatrice Bevilacqua‡, Yangze Zhou‡, Bruno Ribeiro

ICML 2021, Long Talk (166 / 5,513 submissions)

Paper Code

Predicting cellular responses to perturbation across diverse contexts with State

Abhinav K. Adduri, Dhruv Gautam, Beatrice Bevilacqua, Alishba Imran, Rohan Shah, Mohsen Naghipourfar, Noam Teyssier, Rajesh Ilango, Sanjay Nagaraj, Mingze Dong, Chiara Ricci-Tam, Christopher Carpenter, Vishvak Subramanyam, Aidan Winters, Sravya Tirukkovular, Jeremy Sullivan, Brian S. Plosky, Basak Eraslan, Nicholas D. Youngblut, Jure Leskovec, Luke A. Gilbert, Silvana Konermann, Patrick D. Hsu, Alexander Dobin, Dave P. Burke, Hani Goodarzi, Yusuf H. Roohani

bioRxiv 2025

Paper

All In: Bridging Input Feature Spaces Towards Graph Foundation Models

Moshe Eliasof, Krishna Sri Ipsit Mantri, Beatrice Bevilacqua, Carola-Bibiane Schönlieb, Bruno Ribeiro

UniReps 2025

Paper

Zero-shot generalization of gnns over distinct attribute domains

Yangyi Shen, Jincheng Zhou, Beatrice Bevilacqua, Joshua Robinson, Charilaos Kanatsoulis, Jure Leskovec, Bruno Ribeiro

ICML 2025

Paper

Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings

Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec, Bruno Ribeiro

ICLR 2025

Paper Code

TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs

Yucheng Zhang, Beatrice Bevilacqua, Mikhail Galkin, Bruno Ribeiro

LoG 2024

Paper

Digraf: Diffeomorphic Graph-Adaptive Activation Function

Krishna Sri Ipsit Mantri, Xinzhi Wang, Carola-Bibiane Schönlieb, Bruno Ribeiro, Beatrice Bevilacqua‡, Moshe Eliasof‡

NeurIPS 2024

Paper

Granola: Adaptive Normalization for Graph Neural Networks

Moshe Eliasof‡, Beatrice Bevilacqua‡, Carola-Bibiane Schönlieb, Haggai Maron

NeurIPS 2024

Paper

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products

Guy Bar-Shalom, Beatrice Bevilacqua, Haggai Maron

ICML 2024

Paper

Efficient Subgraph GNNs by Learning Effective Selection Policies

Beatrice Bevilacqua, Moshe Eliasof, Eli Meirom, Bruno Ribeiro, Haggai Maron

ICLR 2024

Paper Code

A Multi-Task Perspective for Link Prediction with New Relation Types and Nodes

Jincheng Zhou, Beatrice Bevilacqua, Bruno Ribeiro

NeurIPS GLFrontiers 2023

Paper

Neural Algorithmic Reasoning with Causal Regularisation

Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Veličković

ICML 2023

Paper

Graph Positional Encoding via Random Feature Propagation

Moshe Eliasof, Fabrizio Frasca, Beatrice Bevilacqua, Eran Treister, Gal Chechik, Haggai Maron

ICML 2023

Paper

Causal Lifting and Link Prediction

Leonardo Cotta, Beatrice Bevilacqua, Nesreen Ahmed, Bruno Ribeiro

The Royal Society A

Paper

A Generalist Neural Algorithmic Learner

Borja Ibarz, Vitaly Kurin, George Papamakarios, Kyriacos Nikiforou, Mehdi Bennani, Róbert Csordás, Andrew Dudzik, Matko Bošnjak, Alex Vitvitskyi, Yulia Rubanova, Andreea Deac, Beatrice Bevilacqua, Yaroslav Ganin, Charles Blundell, Petar Veličković

LoG 2022, Spotlight

Paper

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Fabrizio Frasca‡, Beatrice Bevilacqua‡, Michael M. Bronstein, Haggai Maron

NeurIPS 2022, Oral (199 / 10,411 submissions)

Paper Code

Equivariant Subgraph Aggregation Networks

Beatrice Bevilacqua‡, Fabrizio Frasca‡, Derek Lim‡, Balasubramaniam Srinivasan, Chen Cai, Gopinath Balamurugan, Michael M. Bronstein, Haggai Maron

ICLR 2022, Spotlight (174 / 3391 submissions)

Paper Video Code

Size-Invariant Graph Representations for Graph Classification Extrapolations

Beatrice Bevilacqua‡, Yangze Zhou‡, Bruno Ribeiro

ICML 2021, Long Talk (166 / 5,513 submissions)

Paper Code

Simulation-Based Evolutionary Optimization of Air Traffic Management

Alessandro Pellegrini, Pierangelo di Sanzo, Beatrice Bevilacqua, Gabriella Duca, Domenico Pascarella, Roberto Palumbo, Juan Josè Ramos, Miquel Àngel Piera, Gabriella Gigante

IEEE Access 2020

Service

Talks and Tutorials

Experience

Beatrice Bevilacqua
Based on Martin Saveski's template.