Dr. Elor’s research focus is on the analysis of large heterogeneous image collections, a topic that is on the frontier of computer vision research today, and to which she has already made several important contributions. The question she addresses is how to organize visual information in a useful manner.
While working on her PhD from Tel Aviv University in Electrical Engineering, she and her thesis advisor taught the computer graphics, vision, and image-processing course.
For her postdoctoral research in the Computer Science Department at Cornell Tech, Dr. Elor plans to work on gathering computer graphics and vision in unsupervised or semi-supervised settings, where labelled data is unavailable. In semi-supervised settings, she will explore how to leverage deep neural networks to boost clustering performance in challenging multimodal settings. In unsupervised settings, she will work on improving image-to-image translation.
In the past, Dr. Elor has worked as a research scientist in the Amazon AI computer vision team; as a research intern at Facebook, where she dealt with animating human faces, starting from just a single image; and as an image processing engineer at the Israeli government company Rafael Advanced Defense Systems.