Research
When I was a kid, I wanted to be a cop. Then, during my high school years, I wanted to be an actor. Then, during my university years, I wanted to be a scientist.
Then I went to academia, since it was and still is the best way to combine these three careers in a single one.
Research projects come and go, but there is always a common ground between them. My main research field is statistical signal processing, with an emphasis of sparse signals and machine learning developments. My publication list is accessible here. You can also check out my Github profile for some code I made along the way.
Here is a non-exhaustive list of the research I am currently doing. I am always happy to discover other fields and talk about the one I already know; send me a mail and we can talk.
Signal Processing and Machine Learning Methods for Gamma Spectroscopy
I am interested in developing new methods and paradigms for the analysis of signals stemming from nuclear spectroscopy. The goal is to estimate the activity of the radioactive sources and to identify them.
Collaborators: Yann Sepulcre, Dima Bykhovsky, Xiaoying Zheng
Current Students: Zikang Chen (Ph.D. candidate)
Past collaborators: Antoine Souloumiac, Eric Moulines, Francois Roueff, Ya’acov Ritov, Thierry Montagu, Eric Barat, Thomas Dautremer
Past students: Shapir Zaretsky, Yona Cohen, Ilia Gildin, Uriel Aferiat, Michael Rotman, Mor Tal, Yaniv Mashiach
Signal Processing and Machine Learning Methods for Biomedical Signals
I try to apply compressive sensing and machine learning methodologies to gain insight on biomedical data (ECG and epilepsy mostly), to automatically predict atrial fibrillation and epilepsy episodes.
Collaborators: David Luengo, Javier Via, Yirmi Hauptman
Current Students: Matan Masika
Past collaborators: Yuval Bechor
Past students: Shlomi Talala, Shira Levin, Igor Kolesnikov
Signal Processing and Machine Learning Methods for Agriculture and Environmental Problems
Environmental problems and agriculture challenges became the next challenge for scientists. Plus, in Israel, maximizing agricultural yield while minimizing the resources used is paramount. The use of modern techniques for inference can bring further insights.
Collaborators: Ittai Herrmann, Asher Peretz
Current Students: Ashish Mishra (Ph.D. candidate)
Past collaborators:
Past students: Oren Goldberg, Maxim Yirmulenko, Linoi Dahan, Beni Levi