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Dr. Ethan Fetaya’s Machine Learning Lab

About

I joined the Bar-Ilan Engineering faculty in 2019. My research interests span a wide array of topics in machine learning and computer vision. Recently, I have been very interested in topics related to AI safety. More generally topics I worked on include generative models, few-shot learning, deep Bayesian models, multi-task learning, federated learning, and geometric deep learning.

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Fields of Interest

AI safety

Learning with limited supervision

Multitask learning

Recent Publications

Shor, Tamir ; Fetaya, Ethan ; Baskin, Chaim et al. / Adversarial Attacks in Weight-Space Classifiers. In: Transactions on Machine Learning Research. 2026 ; Vol. 2026-February.
Glazer, Neta ; Segal-Feldman, Yael ; Segev, Hilit et al. / Beyond Transcription : Mechanistic Interpretability in ASR. Proceedings of the AAAI Conference on Artificial Intelligence. editor / Sven Koenig ; Chad Jenkins ; Matthew E. Taylor. 44. ed. Association for the Advancement of Artificial Intelligence, 2026. pp. 37407-37416 (Proceedings of the AAAI Conference on Artificial Intelligence; 44).
Cohen, Itay ; Fetaya, Ethan ; Rosenfeld, Amir. / Can Modern Vision Models Understand the Difference Between an Object and a Look-Alike?. In: AI (Switzerland). 2026 ; Vol. 7, No. 4.
Eby, Jonathan ; Beutel, Moshe ; Koivisto, David et al. / Electromyographic typing gesture classification dataset for neurotechnological human-machine interfaces. In: Scientific data. 2025 ; Vol. 12, No. 1.