PhD student in the Electrical Engineering Department, Technion at Israel Institute of Technology
Areas of expertise
- - Sparse and redundant representations
- - Signal and image modeling
- - Deep learning
- - Inverse problems
Convolutional Neural Networks Analyzed via Convolutional Sparse Coding The Little Engine that Could: Regularization by Denoising (RED) RAISR: Rapid and Accurate Image Super Resolution Boosting of Image Denoising Algorithms
Yaniv Romano received his B.Sc. degree from the Department of Electrical Engineering, Technion – Israel Institute of Technology, in 2012, where he is currently pursuing his Ph.D.. He received the 2015 Zeff fellowship, the 2017 Andrew and Erna Finci Viterbi fellowship, and the 2017 Irwin and Joan Jacobs fellowship. In parallel to his studies, he has been working in the industry since 2011 as an Image Processing Algorithm Developer. The super-resolution technology he invented as a researcher in Google was launched in 2017, leading to significant bandwidth savings of billions of images.