Yoav Rubin
Email: rubin.yoav[at]gmail.com
Yoav Rubin received his B.Sc degree in Earth Sciences from the Hebrew University in Jerusalem in 2010, where he specialised in atmospheric science and oceanography. He received his M.Sc. degree in Atmospheric Sciences from Tel-Aviv University in 2019.
Currently, Yoav is a Ph.D. student in Atmospheric Science at the Geophysics department at Tel Aviv University. He continues his research on high-resolution humidity measurement based on commercial microwaves links. In his current research, Yoav focuses on improving the rain forecast by assimilating commercial microwave links measurements for humidity observations in numerical weather prediction models, and study the city/land cover effects on the humidity in the atmosphere.
Hai Victor Habi
Email: haivictorh[at]mail.tau.ac.il
Google scholar: hai habi
Github: haihabi
Hai Victor Habi was born in 1986. He received a B.Sc. degree (cum laude) in Electrical and Electronic Engineering from the Holon Institute of Technology in 2014 and received an M.Sc. degree in Electrical Engineering from Tel Aviv University in 2020.
In his M.Sc., Hai dealt with different aspects of environmental monitoring using machine learning and commercial microwave links.
His current research interests include machine learning, deep learning, and signal processing combining different measurement sources. Hai started his professional career at Altair Semiconductors Ltd., a Sony Company group, Hod Hasharon, Israel, and has become the company’s Deep Neural Network Research and Algorithms Team Leader.
Dror Jacoby
Email: drorjacoby[at]mail.tau.ac.il
Scholar: Dror Jacoby
Office: 110 Electrical engineering laboratory.
Dror Jacoby received his B.Sc. and M.Sc. degrees (with Magna Cum Laude) in Electrical Engineering from Tel-Aviv University through the Accelerated Master Program in 2022.
During the M.Sc. studies, Dror has received Weinstein Prize for research and studies achievements. The M.S.c research focused on the prediction of the attenuation in wireless communication using signal processing and machine learning methods.