Yoav grew up in Jerusalem and lives in Tel Aviv with his wife Gali. After serving in an IDF intelligence unit, he pursued a double BSc in physics and electrical engineering at Tel Aviv University, where he participated in the Adi Lautman Program for Outstanding Students. He graduated summa cum laude from both departments. During his undergraduate studies he conducted physics research at a US DoE particle-accelerator facility and at the Weizmann Institute Atomic Scale Physics lab. There, he encountered the fascinating field of topological phases of matter, and he continued pursuing research in this field from a theoretical perspective as part of his graduate work at the Weizmann Institute. His MSc thesis resulted in a published paper theoretically analyzing a realization scheme for topological phases of matter.

Increasingly intrigued by the field of Artificial Intelligence, which has raised fundamental scientific questions and shown a great potential to impact society, Yoav joined the deep learning theory group at the Hebrew University for his doctoral work. His research aims to shed light on the success of prominent deep learning architectures by using tools from quantum physics, and to promote the use of deep networks for quantum physics research. Yoav has published three theoretical papers establishing novel connections between these fields. The first two provide new insights into prominent deep learning architectures of the kind used for computer vision and speech recognition, while the third proves that deep learning architectures can be employed for the investigation of highly entangled many-body quantum systems.