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I'm an AI Research Scientist at Meta, working mainly on Graph Foundation Models and LLMs post-training with structured data.

I am also a lecturer at the Computer Science School at Tel-Aviv University,  teaching "Machine Learning with Graphs" , an advanced course I have built from scratch to spread the rumor on Graph Machine Learning.
I defended my PhD "Towards improved Generalizability and Interpretability in Graph Neural Networks" at the School of Computer Science at Tel Aviv University, where I was fortunate be advised by  Amir Globerson .

I am broadly interested in Deep Learning and Geometric Deep Learning. 

In the summer of 2021, I interned at Meta.
Prior to that, I spent three years at Microsoft's Machine Learning Incubation and Innovation group (CTO office),  where I had the opportunity to invent, lead and develop novel and disruptive AI-based products.

I hold a BSc and MSc in Computer Science from Ben-Gurion University, where I conducted research with Natan Rubin and participated in the ‘Dkalim’ and ‘Intel’ excellence programs.

I also completed a second full BSc in Mathematics after my MSc and mostly in parallel to my PhD, just for fun. I really love Math.

GraphBench: Next-generation graph learning benchmarking

Timo Stoll, Chendi Qian, Ben Finkelshtein, Ali Parviz, Darius Weber, Fabrizio Frasca, Hadar Shavit, Antoine Siraudin, Arman Mielke, Marie Anastacio, Erik Müller, Maya Bechler-Speicher, Michael Bronstein, Mikhail Galkin, Holger Hoos, Mathias Niepert, Bryan Perozzi, Jan Tönshoff, Christopher Morris

Preprint

SuperMAN: Interpretable and Expressive Networks over Temporally Sparse Heterogeneous Data

Maya Bechler-Speicher*, Andrea Zerio*, Maor Huri, Marie Vibeke Vestergaard, Ran Gilad-Bachrach, Tine Jess, Samir Bhatt, Aleksejs Sazonovs

International Conference on Learning Representations (ICLR) 2026

Graph Mixing Additive Models

Maya Bechler-Speicher*, Andrea Zerio*, Maor Huri, Marie Vibeke Vestergaard, Ran Gilad-Bachrach, Tine Jess, Samir Bhatt, Aleksejs Sazonovs

NeurIPS Symmetry and Geometry in Neural Representations (NeurReps) Workshop 2025

Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

Maya Bechler-Speicher *, Ben Finkelshtein *, Fabrizio Frasca *, Luis Müller *, Jan Tönshoff *, Antoine Siraudin, Viktor Zaverkin, Michael M. Bronstein, Mathias Niepert, Bryan Perozzi, Mikhail Galkin, Christopher Morris

Internation Conference on Machine Learning (ICML) 2025