ICML 2020 paper 'On Learning Sets of Symmetric Elements' received the Outstanding Paper Award
Recipient of the Alon scholarship for the Integration of Outstanding Faculty
Served as Area Chair for NeurIPS 2023
Delivered tutorials at Simons Institute and Learning on Graphs Conference on topics including 'The expressive power of GNNs' and 'Equivariant architectures for learning in deep weight spaces'
Oral presentation at LOG 2025: 'GL Equivariant Metanetworks for Learning on Low Rank Weight Spaces'
Background
Assistant Professor and Robert J. Shillman Fellow at the Faculty of Electrical and Computer Engineering, Technion
Senior Research Scientist at NVIDIA Research, Tel Aviv lab
Primary research interest: machine learning, especially deep learning for structured data
Focuses on applying deep learning to sets, graphs, point clouds, surfaces, weight spaces, and other mathematical objects with inherent symmetry
Research goals: (1) theoretically understand and design deep learning architectures (e.g., expressive power); (2) demonstrate practical effectiveness on real-world structured data problems