Eldar is an algorithm developer, currently focusing on ElliQ’s vision. The goal is to teach ElliQ how to analyze the scene and the social context, using state-of-the-art computer vision and deep learning algorithms.
Eldar has nearly a decade of experience in computer vision R&D, both in the academy and the industry. The formation of his passion for computer vision dates back to his years in Hedva Spitzer's Vision Research Lab in Tel Aviv university. Deeply invested in explaining computationally the phenomena of human visual perception, as expressed in the mechanisms of shape, texture and similarity, he has built computational models based on the known cortical and retinal receptive fields. One of his solid contributions was a computational model for salient contours, which formulated the necessary and sufficient stimulus conditions for illusory shape formation, and yielded the suggestion that chromatic salient contours may exist (that was psychophysically validated in the lab). One of the amazing phenomena that attracted Eldar's attention was the diagnostic ability of radiologists to discriminate pathological tissues from benign, while viewing body images (e.g., mammograms or CT scans) that are textured and of low contrast, and often exhibit occlusions of the pathology by the surrounding tissues.
Eldar holds a M. Sc. in Bio-Medical Engineering and a B.Sc. in Physics & Electrical Engineering from Tel-Aviv University.
I’m a qualified yoga teacher, and practice headstands every morning to maintain my analytic abilities.