Lewiner Institute for Theoretical Physics, room 407
Research interests: I’m interested in condensed matter theory and, in particular, topological phases as well as application of deep learning and self-supervised learning in physics. Currently I focus on edge modes and interfaces in topological state, e.g., Kitaev spin liquid, fractional quantum Hall, p+ip superconductors. I also have a Telegram channel where I post links to research I find interesting.
Previously: I finished CS M.Sc. in Technion, advised by Alex Bronstein, Avi Mendelson, and Chaim Baskin, and studied reduced supervision in computer vision (in particular, self-supervised and semi-supervised learning). I was a research intern in Creative Vision team in Snap Research in Summer 2020, working on 3D reconstruction trained on single 2D views with Olly Woodford and Sergey Tulyakov. Before that, I was part of Rothschild Technion Program for Excellence and received double B.Sc. (CS and Physics+Math, Cum Laude) from Technion. In 2017, I participated in Google Summer of Code under OpenCV organization.
|Mar 28, 2022||Our team “Barren plateau inhabitants” with project “Simulation of anyons within the toric code model” based on “Realizing topologically ordered states on a quantum processor” won second place (out of 46 submitted projects) at QHack 2022 Open Hackathon IBM Qiskit Challenge.|
|Mar 2, 2022||Our paper “End-to-End Referring Video Object Segmentation with Multimodal Transformers” (MTTR) got accepted to CVPR 2022.|
|Jan 13, 2022||Our paper “Weakly Supervised Recovery of Semantic Attributes” got accepted to CLeaR 2022.|
|Oct 4, 2021||Our paper “Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels” (C2D) got accepted to WACV 2022.|
|Aug 26, 2021||Our paper “CAT: Compression-Aware Training for Bandwidth Reduction” got accepted to JMLR.|
CVPR’22End-to-End Referring Video Object Segmentation with Multimodal TransformersIn IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Jun 2022
WACV’22Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsIn IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Jan 2022
workshopSelf-Supervised Learning for Large-Scale Unsupervised Image ClusteringNeurIPS Self-Supervised Learning Workshop Aug 2020