Netanel Ratner, Developer in Yuvalim, Israel
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Netanel Ratner

Verified Expert  in Engineering

Bio

Netanel is a research engineer in machine and deep learning, computer vision, and optimization. He specializes in designing real-time embedded systems, such as high-end AI-integrated imaging systems, and is skilled in C, C++, and Python. Netanel's R&D projects have included medical imaging, solar energy, aerospace and defense, and semiconductors. He has a bachelor's degree in computer engineering and a master's degree in electrical engineering from the Technion – Israel Institute of Technology.

Portfolio

Rafael Advanced Defense Systems
Management, Computer Vision, Machine Learning, Deep Learning...
CSIRO Data61 (Formerly NICTA)
C++, Boost, Machine Learning, Optimization, CMake, Pandas, Data Science...
Samsung Semiconductor Israel R&D Center (SIRC)
Image Processing, Digital Imaging, Management, Software, Research, Realtime...

Experience

  • Image Processing - 20 years
  • C++ - 20 years
  • Computer Vision - 20 years
  • Systems Engineering - 15 years
  • Optimization - 15 years
  • OpenCV - 8 years
  • Deep Learning - 7 years
  • Python - 5 years

Availability

Part-time

Preferred Environment

PyCharm, Visual Studio, Pandas

The most amazing...

...achievement: owning a unique patent in computational photography, dealing with optimal multiplexing codes for computational photography and other applications.

Work Experience

CTO of Computer Vision and Electro-optics

2014 - PRESENT
Rafael Advanced Defense Systems
  • Led the development of a contest-winning prototype of an autonomous drone.
  • Developed a unique intelligence-gathering system.
  • Led the design of a high-end seeker head of an autonomous missile.
  • Introduced and integrated novel deep learning-based methods for tracking, simultaneous localization and mapping (SLAM), and image enhancement.
  • Trained and mentored junior computer vision engineers.
  • Initiated collaboration with the academy and other research groups.
Technologies: Management, Computer Vision, Machine Learning, Deep Learning, Simultaneous Localization & Mapping (SLAM), Drones, Image Processing, Training, Data Science, Object Detection, Object Tracking, Python, Artificial Intelligence (AI), Azure, Image Analysis, Algorithm Design, Data Analysis, Data Analytics, You Only Look Once (YOLO)

Research Officer

2013 - 2014
CSIRO Data61 (Formerly NICTA)
  • Designed a system for the distributed prediction of cloud cover to predict solar power production capacity.
  • Invented a novel method for cloud cover prediction using optic flow.
  • Performed hands-on, end-to-end R&D, from the selection of the optics to writing the entire code for a client-server prediction system.
Technologies: C++, Boost, Machine Learning, Optimization, CMake, Pandas, Data Science, Object Tracking, Python, Artificial Intelligence (AI), Image Analysis, Edge Computing, Algorithm Design, Data Analysis, Data Analytics

Image and Signal Processor (ISP) Algorithms Team Leader

2011 - 2013
Samsung Semiconductor Israel R&D Center (SIRC)
  • Led a group of several engineers to develop an image processing algorithm chain for a system-on-a-chip (SoC).
  • Personally developed and implemented an auto-focus algorithm.
  • Trained and mentored junior computer vision engineers. Some became team leaders.
Technologies: Image Processing, Digital Imaging, Management, Software, Research, Realtime, Training, System-on-a-Chip (SoC), Algorithms, Python, Image Analysis, Edge Computing, Algorithm Design, Data Science, Data Analysis, Data Analytics

Experience

Deep Learning-based Melanoma Self-identification

https://www.rmmj.org.il/issues/36/816/manuscript
Mentored and supervised two undergraduate students in a project designed to classify Melanoma skin cancer from benign lesions using simply visual wavelength imagery. Training a convolutional neural network yielded good results with a relatively small amount of data. This work has been presented and published on a dedicated research day.

Automatic Refueling System

Performed system engineering and system architecture, including hands-on coding of a robotic refueling system based on 2D and 3D cameras. This included selecting and positioning the cameras, designing the software architecture, and implementing the algorithmic core of the object detection and registration algorithms.

Medical Image Enhancement

Designed and implemented a deep learning-based algorithm for image enhancement of a miniature camera for laparoscopic surgery. The algorithm was based on an existing network architecture, modified to comply with execution in real time on existing hardware, and retrained on relevant imagery. The training process was performed on a cloud platform.

ANU-NICTA Solar Forecasting Pilot Project

https://data.csiro.au/collection/csiro:41758
This project used visual information obtained from sky-facing cameras and power production readings from solar panels to predict future solar power production. The project included end units of a camera, a NUC computer, a wireless communication module, and a server fusing and processing the data sent from the end units to make the predictions.

Soft Tissue Point Tracker

Designed and implemented a point tracker for laparoscopic surgery. It was designed to track, with pinpoint accuracy, a point located on a soft, non-rigid tissue while operating on this tissue using delicate tools. The tracker was robust to short occlusions and image clutter. It was implemented using the ITK medical imaging open source.

Education

2001 - 2007

Master's Degree in Electrical Engineering (summa cum laude)

Technion – Israel Institute of Technology - Haifa, Israel

1997 - 2001

Bachelor's Degree in Computer Engineering (cum laude)

Technion – Israel Institute of Technology - Haifa, Israel

Certifications

OCTOBER 2019 - PRESENT

Deep Learning Specialization

Coursera

Skills

Libraries/APIs

PyTorch, Scikit-learn, OpenCV, TensorFlow, Keras, Pandas

Tools

Algorithm Design, Visual Studio, You Only Look Once (YOLO), PyCharm, CMake, ITK

Languages

C++, Python, C

Frameworks

Realtime, Boost

Paradigms

Management

Platforms

Azure

Other

Image Processing, Computer Vision, Machine Learning, Data Science, Object Detection, Object Tracking, Artificial Intelligence (AI), Data Scientist, Statistical Analysis, Image Analysis, Data Analysis, Data Analytics, Programming, Optimization, Research, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNNs), Deep Learning, Systems Engineering, Software, Edge Computing, Signal Processing, Writing & Editing, Recurrent Neural Networks (RNNs), Transformers, Big Data, Digital Imaging, Medical Imaging, Simultaneous Localization & Mapping (SLAM), Drones, Training, System-on-a-Chip (SoC), Algorithms, Point Clouds, Image Registration, Software Architecture, Tracking, Mentorship & Coaching, Classification Algorithms, Medical Diagnostics

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