Tal Amir’s Homepage

I am a research associate at the Faculty of Mathematics, Technion, working with Dr. Nadav Dym.

My main research interests are machine learning and optimization, with a focus on developing mathematical tools to enable deep learning on structured data such as sets, point clouds, and graphs. More info

I completed my Ph.D. in 2020 under the supervision of Prof. Boaz Nadler at the Department of Computer Science and Applied Mathematics in the Weizmann Institute of Science.

Research Highlights

• Developed a state-of-the-art method for sparse signal recovery. [2021, SIMODS]

• Developed the first injective Euclidean embedding for multisets and measures based on neural functions. [2023, NeurIPS spotlight]

• Developed the first bounded-distortion Euclidean embedding for multisets, and proved a fundamental impossibility result for such embeddings on distributions. [2025, ICLR]

• Showed that oversquashing in graph neural networks is not limited to long-range tasks. [2025, LoG Best Paper Award]

• Currently working on developing a low-distortion rotation-invariant Euclidean embedding for 3D point clouds and molecular data.