Beatrice Bevilacqua
Scholar

Beatrice Bevilacqua

Google Scholar ID: RvtEObEAAAAJ
PhD Candidate, Purdue University
Geometric Deep LearningInvariant RepresentationsGraph Neural Networks
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Citations & Impact
All-time
Citations
854
 
H-index
11
 
i10-index
12
 
Publications
20
 
Co-authors
6
list available
Contact
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Publications
3 items
Boosting Relational Deep Learning with Pretrained Tabular Models
2025
Cited
0
TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs
2025
Cited
0
On the Effectiveness of Random Weights in Graph Neural Networks
2025
Cited
0
Resume (English only)
Academic Achievements
  • Published multiple papers in conferences such as ICLR 2025, NeurIPS 2024, ICLR 2024, ICML 2023, NeurIPS 2022, ICLR 2022, and ICML 2021.
Research Experience
  • Research Scientist Intern at DeepMind (Fall 2022), collaborating with Dr. Petar Veličković on Neural Algorithmic Reasoning.
Education
  • Ph.D. in Computer Science from Purdue University, advised by Prof. Bruno Ribeiro, and also working closely with Prof. Haggai Maron.
Background
  • Ph.D. Candidate in Computer Science at Purdue University, with research interests in foundation models for structured data, invariances, and reasoning.
Co-authors
6 total
Bruno Ribeiro
Bruno Ribeiro
Associate Professor of Computer Science at Purdue University
Haggai Maron
Haggai Maron
Assistant Professor at the Technion, Research Scientist at NVIDIA Research
Michael Bronstein
Michael Bronstein
DeepMind Professor of AI, University of Oxford / Scientific Director, AITHYRA
Petar Veličković
Petar Veličković
Senior Staff Research Scientist, Google DeepMind | Affiliated Lecturer, University of Cambridge
Jure Leskovec
Jure Leskovec
Professor of Computer Science, Stanford University
Mikhail Galkin
Mikhail Galkin
Research Scientist, Google