Aviv Netanyahu

I am a PhD student in EECS at MIT CSAIL, advised by Prof. Pulkit Agrawal, as part of the Improbable AI Lab.

I earned my MSc from the Faculty of Mathematics and Computer Science at the Weizmann Institute of Science, advised by Prof. Shimon Ullman, where I worked on Computer Vision. Before that, I received my BSc in Mathematics and Computer Science from the Hebrew University of Jerusalem.

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I am interested in studying how to deploy agents in new environments with minimum to no supervision. My research focuses, in this context, on inferring how agents interact with the environment and with other agents in ways that are generalizable to new settings. Issues related to this research include combinatorial and out-of-distribution generalization, object-centric learning, and learning from demonstrations.

Graph-based one-shot reward learning via active learning for object rearrangement tasks.

A dataset for inferring physically grounded social interactions between two agents.

Extraction and representation of scene components, such as objects and their parts, people, and places, individual properties, and relations and interactions between them by combining bottom-up and top-down networks, interacting through a symmetric bi-directional communication between them.

A system for selective visual relationship detection that achieves out-of-distribution and combinatorial generalization.

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