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 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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Master's 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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Keren Cohen, M.Sc. Student (with Dr. Tamir Bendory, TAU)

Topic: Deep learning for Cryo-EM / MRA

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

Topic: Phenomena in feature learning

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Netanel Daniel, M.Sc. Student (with Dr. Ofir Lindenbaum)

Topic: Efficient transformer

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

Topic: Improved fine-tuning

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Interns:

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Amit Levy, B.Sc. Student

Topic: Learning to denoise without clean data

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Roy Turgeman, B.Sc. Student

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

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Ariel Fargion, B.Sc. Student

Topic: Enhancing conformal prediction

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Alumni:

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

Thesis: "Multiple Descents in Unsupervised Learning"

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Colleagues that I informally co-advised and still do research with:

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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)

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