Team​

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I'm alway looking for self-motivated graduate students with strong academic record that are interested in doing research on theory and applications in the fields of machine (deep) learning, signal & image processing, optimization, and their interconnections.

If you are interested in joining my research group, you are more than welcome to send me an email with your CV and academic record.

Please note: I'm not considering candidates who are employed full-time in industry positions. 

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Current Lab Members

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M.Sc. Students:

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Tomer Garber, M.Sc. Student

Topic: Solving inverse problems with diffusion models

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Lahav Dabah, M.Sc. Student (direct track)

Topic: Uncertainty quantification: confidence calibration & conformal prediction

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Lioz Berman, M.Sc. Student (with Prof. Sharon Gannot)

Topic: Deep learning for array processing​​

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Omer Vigder, M.Sc. Student (with Dr. Ofir Lindenbaum)

Topic: Phenomena in feature learning

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Yahav Cohen, M.Sc. Student

Topic: Uncertainty quantification in regression

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Ariel Fargion, M.Sc. Student

Topic: Enhancing conformal prediction

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Research Assistants:

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​Roy Turgeman

Topic: On the relation between low- and high-level tasks

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Alumni

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Former M.Sc.:

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Idan Mashiach, M.Sc., 2025 (with Dr. Oren Glickman)

Thesis: "Catastrophic Forgetting Mitigation Through Plateau Phase Activity Profiling"

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Kobi Rahimi, M.Sc., 2025 (with Dr. Ofir Lindenbaum)

Thesis: "Multiple Descents in Unsupervised Learning"

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Former B.Sc.:

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Roy Turgeman, B.Sc., 2025 ---> Research Assistant

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Ariel Fargion, B.Sc., 2025 ---> M.Sc. Student

 

Amit Levy, B.Sc., 2025

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Lahav Dabah, B.Sc., 2024 ---> Direct M.Sc. Track

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Alumni that I informally co-advised:

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Shady Abu-Hussein, Ph.D. (with Prof. Raja Giryes, TAU)

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Vignesh Kothapalli, M.Sc. (with Prof. Joan Bruna, NYU) ---> LinkedIn ---> Ph.D. Student at Stanford

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