Itamar is available for hire

Itamar Tsayag

Verified Expert in Engineering

Computer Vision Algorithm Developer

Location

Tel Aviv-Yafo, Israel

Toptal Member Since

February 25, 2022

Itamar是一位才华横溢的算法开发人员和数据爱好者，拥有计算机视觉方面的专业知识, machine learning, and statistical analysis. 他已经成功地部署了尖端的算法，以提高试管婴儿周期的疗效和中风诊断. With a master's degree in electrical engineering and data science, Itamar擅长阐述复杂的主题和推动有影响力的结果, leveraging his technical prowess and business acumen.

Portfolio

AIVF

Videos, Python, PyTorch Lightning, Optimization, Embryology...

Viz.ai

Python，深度学习，计算机视觉算法，分析学，数据库...

Defense Companies (Classified)

Python，视频处理，图像处理，光学传感器，深度学习...

Experience

Deep Learning - 7 years Python - 6 years PyTorch - 5 years Data Science - 5 years Research - 4 years Algorithms - 4 years Computer Vision Algorithms - 3 years Medical Imaging - 2 years

Availability

Part-time

Preferred Environment

Ubuntu Linux, PyCharm, Visual Studio Code (VS Code), Amazon EC2, PIP, Git, Bitbucket, Vim Text Editor, MacOS, Stock Trading

The most amazing...

...我的经验是研究和开发一种神经网络压缩算法，用于性能相当的小型网络.

Work Experience

Lead Algorithm Developer

2022 - 2023

AIVF

开发了用于提高IVF周期效率的胚胎分级算法的SW和ML流水线.
在复杂的显微镜图像数据集上利用尖端视频分类和分割网络的算法.
创造了一种算法，并成功部署为公司的旗舰产品, demonstrating strong expertise in code productization.

Technologies: Videos, Python, PyTorch Lightning, Optimization, Embryology, Visual Studio Code (VS Code), Vim Text Editor, ClearML, Data Science, Data Scientist, Scikit-learn, Matplotlib, Data Extraction, Visualization, Open Neural Network Exchange (ONNX), Health, Startups, Data Analytics, Statistical Analysis, Data Reporting, Research, XLSX File Processing, Microsoft Excel, Monte Carlo Simulations, CSV File Processing, Data Cleansing, Data Structures, Data Modeling, Regression Modeling, Large Data Sets, Parallelization, Feature Engineering, Cloud, Data Engineering, Data Pipelines, Pattern Recognition, Machine Vision, API Integration, Minimum Viable Product (MVP), Model Development, Transformers, Technical Leadership, AI Modeling, AI Model Training

Senior Computer Vision Algorithm Developer

2020 - 2022

Viz.ai

开发了一种算法，在中风的情况下区分受损脑组织和健康脑组织.
Oversaw the entire project from annotation guidelines, database structure, system architecture, and SW development to training deep learning models.
监督软件质量，并担任技术领导，包括代码审查、打包和结构.
Managed the tasks of a ten-member team using Jira. The team included data managers and algorithm developers.

Technologies: Python，深度学习，计算机视觉算法，分析学，数据库, Software, Algorithms, PyTorch, Amazon Web Services (AWS), Convolutional Neural Networks (CNN), TensorFlow, Keras, Artificial Intelligence (AI), Software Architecture, Jira, Slack, Machine Learning, Image Analysis, Jupyter Notebook, Classification Algorithms, APIs, Artificial Neural Networks (ANN), Neural Networks, JSON, Functional Programming, DevOps, Terraform, Decision Trees, Pytest, Unit Testing, Object-oriented Programming (OOP), Git, GitHub, Team Leadership, Medical Imaging, Ubuntu Linux, PyCharm, PIP, OpenCV, Cron, CSV, Pandas, NumPy, Data Analysis, Statistics, Jupiter, Amazon EC2, Amazon S3 (AWS S3), Docker, Back-end, Back-end Development, Linux, AI Programming, Healthcare, AWS DevOps, Codebase Development, Data Visualization, Plotly, Amazon SageMaker, Automation, JupyterLab, XGBoost, Random Forests, 2D, GPU Computing, Graphics Processing Unit (GPU), 2D Modeling, Machine Learning Operations (MLOps), Test-driven Development (TDD), Deep Neural Networks, Computer Vision, 3D, Distributed Computing, Data Loading, Machine Learning Automation, Supervised Machine Learning, Videos, Visual Studio Code (VS Code), Vim Text Editor, ClearML, Data Scientist, Scikit-learn, Matplotlib, Data Extraction, Visualization, Open Neural Network Exchange (ONNX), Health, Startups, Data Analytics, Statistical Analysis, Data Reporting, Research, XLSX File Processing, Microsoft Excel, Object Detection, CSV File Processing, Data Cleansing, Data Modeling, Regression Modeling, Large Data Sets, Parallelization, Feature Engineering, Cloud, Data Engineering, Pattern Recognition, Numba, Python Performance, Machine Vision, API Integration, Minimum Viable Product (MVP), Model Development, Technical Leadership, Data Scraping, AI Modeling, AI Model Training

Computer Vision Algorithm Engineer

2020 - 2021

Defense Companies (Classified)

开发了一种在多传感器视频中实时检测物体的算法.
增强地理对象作为视频图像上的地标，采用三维LLA到二维坐标投影.
Used the algorithm to support detection and tracking, 实现每秒高视频帧数(FPS)，并支持RGB和热红外图像的多个视频域.

Technologies: Python，视频处理，图像处理，光学传感器，深度学习, Computer Vision Algorithms, PyTorch, Amazon Web Services (AWS), Convolutional Neural Networks (CNN), TensorFlow, Keras, Machine Learning, Image Analysis, Jupyter Notebook, Classification Algorithms, Artificial Intelligence (AI), APIs, Artificial Neural Networks (ANN), Neural Networks, JSON, Functional Programming, Decision Trees, Object-oriented Programming (OOP), Git, GitHub, Ubuntu Linux, PyCharm, PIP, OpenCV, Cron, CSV, Pandas, NumPy, Data Analysis, Statistics, Jupiter, Amazon EC2, Fine-tuning, Linux, AI Programming, Codebase Development, Data Visualization, Plotly, Automation, JupyterLab, XGBoost, Random Forests, 2D, GPU Computing, Graphics Processing Unit (GPU), Machine Learning Operations (MLOps), Deep Neural Networks, Computer Vision, Analytics, Data Loading, Machine Learning Automation, Supervised Machine Learning, Visual Studio Code (VS Code), Vim Text Editor, Data Science, Data Scientist, Scikit-learn, Matplotlib, Data Extraction, Integration, Visualization, Open Neural Network Exchange (ONNX), Startups, Statistical Analysis, Optimization Algorithms, Microsoft Excel, CSV File Processing, Data Cleansing, Regression Modeling, Large Data Sets, Feature Engineering, Numba, Python Performance, Machine Vision, Model Development, Data Scraping, Physics, Optical Systems, AI Modeling, Scraping, AI Model Training

Senior R&D Engineer

2018 - 2020

Magic Leap

开发了一种新型飞行时间(ToF)深度传感器的校准程序和算法. 所有校准都是工厂准备的最低硬件要求和高性能要求.
采用欧拉视频放大(EVM)算法，通过Magic Leap头戴式耳机的眼球追踪摄像头来估计用户的心率. 这是将耳机用于医疗目的可行性初步研究的一部分.
分析跨平台数据，以支持有关头戴式显示器开发的关键架构决策.
开发了一种生成合成校准向量的方法，使头戴式显示器能够在现实的边缘情况下进行性能测试校准场景.

Technologies: Python, Sensor Fusion, Sensor Data, Optical Sensors, Simulations, Computer Vision Algorithms, Statistical Methods, Calibration, Deep Learning, Architecture, Hardware, Machine Learning, Computer Vision, PyTorch, Convolutional Neural Networks (CNN), Depth Sensors, Image Analysis, Jupyter Notebook, Artificial Neural Networks (ANN), Neural Networks, JSON, Decision Trees, Object-oriented Programming (OOP), Git, GitHub, Ubuntu Linux, PyCharm, PIP, OpenCV, CSV, Pandas, NumPy, Data Analysis, Statistics, Jupiter, Linux, AI Programming, Data Visualization, Plotly, Monte Carlo Simulations, JupyterLab, Random Forests, GPU Computing, Graphics Processing Unit (GPU), Deep Neural Networks, Analytics, Facial Recognition, Data Loading, FFmpeg, Supervised Machine Learning, Visual Studio Code (VS Code), Vim Text Editor, Data Science, 3D Pose Estimation, Data Scientist, Matplotlib, Integration, Startups, Statistical Analysis, Optimization Algorithms, Microsoft Excel, CSV File Processing, Data Cleansing, Regression Modeling, Large Data Sets, Feature Engineering, Machine Vision, Data Scraping, Digital Elevation Models, GIS, Physics, Optical Systems

Experience

Facial Landmark Detection Using Visual Transformers

研究了视觉变形算法在人脸特征检测中的应用. The goal was to improve the performance on faces with occlusions, which was previously hindered by the heatmap regression method. 变压器通过自我注意改善了遮挡地标的结果，但在处理无遮挡的人脸图像时导致误差增加.

Uncovering a Winning Lottery Ticket with Stochastic Gates

A novel pruning technique based on stochastic gates was developed. By leveraging this approach on over-parametrized neural networks, 在没有任何额外训练的情况下，发现了能够获得与目标网络相当结果的子网络. 这项研究为在保持性能的同时降低计算成本和内存需求提供了一条有前途的途径, 利用神经网络在各个领域都有实际的好处.

EyeRate: Estimating Heart BPM Using AR HMD

EyeRate是一个自主项目，它利用了Magic Leap头戴式设备的眼球追踪摄像头. 目标是使用欧拉视频放大算法来估计用户的心率. The project involved understanding the headset's capabilities, implementing the algorithm, 并开发了处理眼动摄像头数据的软件模块. Through testing and refinement, 该项目通过放大血液流动引起的颜色变化，成功估算出心率. EyeRate展示了眼球追踪技术在非侵入性健康监测方面的潜力.

Research in the Field of Animation Automation

我进行这项研究是为了评估一个旨在简化儿童动画创作过程的MVP的可行性. 核心理念是利用人形动画角色的多个图像作为输入, 最终目标是制作出一个以该角色为特色的优秀动画. 为实现这一目标，探索了两种主要和不同的方法.

第一种方法以利用2D图像动画网络为中心. 对这一类别下的方法进行了全面的探索，以衡量它们在减少动画创作所需时间方面的有效性.

与此同时，第二种方法深入到3D角色创建领域. Notably, 市场上有各种复杂的软件，能够为3D人物注入逼真的运动. As such, 主要的挑战是从提供的动画角色的多视角和多姿态图像中生成3D化身. 这一探索涉及到将静态图像无缝转换为动态图像的技术, fully-fledged 3D animations, capitalizing on existing motion-enabling software resources.

Education

2019 - 2022

Master's Degree in Electrical Engineering

Bar-Ilan University - Ramat Gan, Israel

2010 - 2014

Bachelor's Degree in Electrical Engineering

Tel Aviv University - Tel Aviv, Israel

Skills

Libraries/APIs

PyTorch, Pandas, NumPy, XGBoost, Scikit-learn, Matplotlib, OpenCV, TensorFlow, Keras, FFmpeg, PyTorch Lightning

Tools

Git, GitHub, Plotly, PyCharm, Jira, Pytest, Cron, Microsoft Excel, Bitbucket, Vim Text Editor, Slack, Terraform, Amazon SageMaker, GIS

Languages

Python

Paradigms

Data Science, Functional Programming, Unit Testing, Object-oriented Programming (OOP), Automation, Test-driven Development (TDD), Distributed Computing, DevOps

Platforms

Ubuntu Linux, Amazon EC2, Jupyter Notebook, Visual Studio Code (VS Code), ClearML, Amazon Web Services (AWS), Linux, MacOS, Docker, NVIDIA CUDA

Industry Expertise

Healthcare

Storage

JSON, Amazon S3 (AWS S3), Databases, Data Pipelines

Other

Deep Learning, Machine Learning, Software, Computer Vision, Convolutional Neural Networks (CNN), Artificial Intelligence (AI), Classification Algorithms, Artificial Neural Networks (ANN), Neural Networks, CSV, Data Analysis, Data Visualization, Monte Carlo Simulations, Random Forests, Supervised Machine Learning, Data Scientist, Startups, CSV File Processing, Machine Vision, Minimum Viable Product (MVP), Model Development, AI Model Training, Image Processing, Digital Signal Processing, Probability Theory, Research, Computer Vision Algorithms, Calibration, Medical Imaging, PIP, Algorithms, Analytics, Depth Sensors, Software Architecture, Image Analysis, 3D Pose Estimation, APIs, Decision Trees, Statistics, Jupiter, Fine-tuning, AI Programming, Codebase Development, Image Recognition, JupyterLab, 2D, GPU Computing, Graphics Processing Unit (GPU), 2D Modeling, Machine Learning Operations (MLOps), Deep Neural Networks, Facial Recognition, Data Loading, Machine Learning Automation, Videos, Data Extraction, Visualization, Open Neural Network Exchange (ONNX), Health, Data Analytics, Statistical Analysis, XLSX File Processing, Data Cleansing, Data Structures, Data Modeling, Regression Modeling, Large Data Sets, Parallelization, Feature Engineering, Cloud, Pattern Recognition, Writing & Editing, Content Writing, Numba, Python Performance, API Integration, Transformers, Technical Leadership, Data Scraping, Physics, Optical Systems, AI Modeling, AI Research, Optimization, Linear Algebra, Calculus, Applied Mathematics, Hardware, Statistical Methods, Sensor Fusion, Sensor Data, Optical Sensors, Simulations, Architecture, Video Processing, Estimations, Google Colaboratory (Colab), Team Leadership, Back-end, Back-end Development, AWS DevOps, 3D, Consulting, Embryology, NN Compression, Integration, Data Reporting, Optimization Algorithms, Generative Adversarial Networks (GANs), Natural Language Processing (NLP), Avatars, Motion AI, Computer Graphics, Object Detection, Stock Trading, Data Engineering, Digital Elevation Models, Scraping, Chief AI Officer

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