CV

Education

2016-Present: Ph.D. Electrical Engineering, Tel Aviv University, Israel 2007-2011: B.Sc. Electrical Engineering, Technion, Israel

Work experience

2016-2017: Co-founder – Fast Imaging

• A startup commercializing research on deep learning for image enhancement
• Funded by Samsung 2015-2017 Co-founder & CTO – Inka Robotics
• A startup developing a vision-based autonomous tattooing robot
• Led the technical team developing algorithms, software & micro-controllers
• Turn it from idea to a working prototype (that tattooed my leg) 2013-2016 Computer Vision Algorithm Engineer – Microsoft  Worked on the HoloLens Project (augmented reality smart glasses)  Part of an incubation team – fast development of PoC for innovative technologies  Developed computer vision algorithms for 3D cameras and Gaze tracking  Developed algorithms in Matlab & performance critical implementations in C++ 2011-2013 ASIC Engineer – Qualcomm  Formal verification technical lead  Functional verification 2008-2011 ASIC Engineering Intern – IBM  ASIC formal and functional verification 2002-2005 Military Service - Combat military service in the Armored Corps, IDF

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

DeepISP: Learning End-to-End Image Processing Pipeline

NICE: Noise Injection and Clamping Estimation for Neural Network Quantization

Delta-encoder: an effective sample synthesis method for few-shot object recognition

Baby steps towards few-shot learning with multiple semantics

RepMet: Representative-based metric learning for classification and one-shot object detection

Beholder-GAN: Generation and Beautification of Facial Images with Conditioning on Their Beauty Level

UNIQ: Uniform Noise Injection for Non-Uniform Quantization of Neural Networks

MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification

Fine-grained Angular Contrastive Learning with Coarse Labels

ISP Distillation

StarNet: towards weakly supervised few-shot detection and explainable few-shot classification

Talks

Intro to AI

May 01, 2017

Talk at HASOUB Hackathon, Nazeret, Israel

Learning an End-to-End Image Processing Pipeline

May 01, 2018

Talk at Data science Summit, Tel Aviv Convention Center, Tel Aviv, Israel

Learning an End-to-End Image Processing Pipeline

June 01, 2018

Seminar at Tel Aviv University, Tel Aviv, Israel

Neural Networks Quantization

June 01, 2018

Talk at Samsung Israel R&D Center, Ramat Gan, Israel

Delta-encoder: an effective sample synthesis method for few-shot object recognition

October 19, 2018

Seminar at Geometric Computing LAB, Stanford University, CA, USA

Delta-encoder: an effective sample synthesis method for few-shot object recognition

December 05, 2018

Spotlight at NeurIPS 2018, Montreal, Canada

Learning an End-to-End Image Processing Pipeline

May 01, 2019

Talk at Rafael & Technion CS Department joint seminar - See Beyond Reality, Technion, Haifa, Israel

Few-shot learning with multiple semantics

June 15, 2019

Presentation at CVPR 2019 Language And Vision Workshop, CA, USA

Delta-encoder: an effective sample synthesis method for few-shot object recognition

November 18, 2019

Talk at AI Week, Tel Aviv, Israel

Small-Data in the Big-Data Era

February 27, 2020

Talk at The 6th Ambassadors' Summit, Tel Aviv University, Tel Aviv, Israel

Teaching

Teaching experience 1

Teaching experience 2

Service and leadership

• Currently signed in to 43 different slack teams