- Idit Diamant (co-supervised with Hayit Greenspan)
- Shlomi Chazan (co-supervised with Sharon Gannot)
- Alan Joseph Bekker
- Oren Melamud
- Amir Alush
- Eyal Schnarch
- Jonathan Berant
- Oded Kaminsky
- Lev Faivishevsky
- Sharon Nissimov
- Roey Mechrez
- Avishay Friedman
- Oren Freifeld
- Jeremie Dreyfuss
- Omer Rotem
- Moshe Taieb
- Amit Ruf
- Shiri Gordon
- Arnaldo Mayer
Information for prospective students
I am looking for highly qualified MSc and PhD students to work on machine learning topics (see my publications for some of my specific interests). While there are a variety of backgrounds that are appropriate for working in my lab, as strong a background in probability and statistics as possible is good, as is the ability to code real systems. Experience with machine learning is also helpful. My lab combines research on machine learning fundamentals with applications to problems in science and engineering:
- Deep learning methods for training and architecture construncting.
- Clustering, classification and dimensionality-reduction.
- Computer vision applications: image and video segmentation, medical imaging.
- Speech and speaker recognition.
- Natural Language Processing (NLP)
Prospective students interested in a research assistantship should email me a letter that describes their background, experience, and research goals. Please also include a list of the courses you have taken (and grades received) and a resume. Attach copies of any papers that you have published in English.