Nour Helal, Developer in Cairo, Cairo Governorate, Egypt
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Nour Helal

Verified Expert  in Engineering

Machine Learning Engineer and Developer

Cairo, Cairo Governorate, Egypt

Toptal member since July 12, 2023

Bio

Nour is a skilled professional focused on artificial intelligence. He has three years of experience leading development teams and seven years of experience designing and developing machine learning models and computer vision algorithms. He has also focused on computer vision to help autonomous cars and drones in environment inception and decision-making steps. Nour has applied AI to military applications, surveillance systems, optical character recognition, drones, and self-driven cars.

Portfolio

Fotopia
Research, Machine Learning Operations (MLOps), Team Management
Fotopia
Tesseract, EasyOCR, OpenCV, PyTorch, Azure Cloud Services, Image Analytics...
Egyptian Armed Forces Research Authority
Digital Imaging, Deep Learning, Computer Vision...

Experience

  • Python - 10 years
  • OpenCV - 8 years
  • Deep Learning - 8 years
  • C++ - 7 years
  • Computer Vision - 6 years
  • PyTorch - 5 years
  • Team Management - 3 years
  • Machine Learning Operations (MLOps) - 1 year

Availability

Part-time

Preferred Environment

Linux, PyTorch, Python, Python 3, OpenCV, NumPy, Azure, Computer Vision, C++, PX4 Autopilot

The most amazing...

...project I've handled successfully as a team lead is the creation of a level-three self-driving car from scratch.

Work Experience

Machine Learning Team Lead

2023 - PRESENT
Fotopia
  • Led the machine learning team to empower our stack of five products with artificial intelligence.
  • Managed the research and development team to develop our new Arabic OCR model and document classifier.
  • Handled the internship program curriculum and road map.
  • Taught advanced deep learning and computer vision modules in our team training program.
Technologies: Research, Machine Learning Operations (MLOps), Team Management

Senior Machine Learning Engineer

2022 - 2023
Fotopia
  • Developed an Arabic OCR-based product from scratch that the user can train to recognize specific documents.
  • Built a product that can detect documents in images, classify document types, fix transformation defects, fix zone positions, retrieve textual data, perform post-processing and OCR post-correction, and export retrieved data to other platforms.
  • Mentored junior developers to empower their knowledge in the field of AI.
Technologies: Tesseract, EasyOCR, OpenCV, PyTorch, Azure Cloud Services, Image Analytics, Image Analysis, Image Processing, Convolutional Neural Networks (CNNs), Deep Learning

Mid-senior Computer Vision Engineer

2021 - 2022
Egyptian Armed Forces Research Authority
  • Developed an Arabic OCR system to digitize legacy paperwork for the Egyptian Ministry of Defense.
  • Built a product to automate the new soldiers' registration and enrollment process via OCR-ing national ID cards.
  • Designed and implemented multiple computer vision algorithms and deep learning techniques to improve military surveillance systems.
Technologies: Digital Imaging, Deep Learning, Computer Vision, Convolutional Neural Networks (CNNs)

Machine Learning Team Lead

2021 - 2022
iSoft Land, Inc.
  • Designed a smart ecosystem to build, train, validate, and deploy machine learning algorithms and deep learning models that control aerial vehicles.
  • Led a team of robotics and deep learning engineers to make a drone fly autonomously within urban environments.
  • Managed a team of robotics and deep learning engineers through specific complex processes related to making a drone fly within urban environments.
Technologies: Team Management

Mid-senior Computer Vision Engineer

2020 - 2021
iSoft Land, Inc.
  • Developed cutting-edge computer vision algorithms that enabled a drone to find the optimal, free takeoff point using an up-facing depth camera.
  • Built a system for the drone to find the optimal landing point underneath using a deep learning depth estimation model.
  • Collaborated with the robotics team to help in solving sensor fusion-related problems.
Technologies: Computer Vision, Robotics, Digital Imaging, Image Analytics, Image Analysis, Convolutional Neural Networks (CNNs), Deep Learning

Machine Learning Engineer

2019 - 2020
iSoft Land, Inc.
  • Developed algorithms to control a drone and connect it to a simulation that teaches school students about drone development.
  • Collaborated with the robotics team to solve various sensor-related problems.
  • Made test fields to test the performance of the drones.
Technologies: Computer Vision, Robotics, Simulations, Convolutional Neural Networks (CNNs)

Deep Learning Engineer

2017 - 2019
Phoenix Team
  • Made a level-three self-driving car for Ain Shams University. It can navigate safely within the campus to help people with special needs.
  • Developed a deep reinforcement learning model from the PPO2 algorithm to control the vehicle.
  • Trained the model using multiple agents on the cloud. A single front-facing RGB camera was the only source feeding this model with additional segmentation and feature extraction models to help with scene understanding.
Technologies: Deep Reinforcement Learning, Computer Vision, Robotics, Cloud, Image Processing, Convolutional Neural Networks (CNNs), Deep Learning

Machine Learning Engineer

2016 - 2017
Freelance
  • Applied machine learning to vision systems in self-driven cars.
  • Performed multiple projects related to facial recognition.
  • Conducted investigations and worked on various projects related to object detection and recognition.
Technologies: Machine Learning, Image Processing, Convolutional Neural Networks (CNNs), TensorFlow, Image Analysis, Deep Learning

Experience

Vision-based Self-navigation System for Autonomous Vehicles

A simulation-oriented vision-based solution that I developed. It can perceive the surrounding environment, fuse multiple cameras, construct a 3D vector map of the environment, and do path planning and routing.

Vision-based In-cabin Monitoring System

An in-cabin monitoring system that I developed that only uses a smartphone's camera. The system includes:

• Gaze tracking and distraction detection.
• Facial expressions and mood classification for model selection and switching between manual and autonomous driving modes.
• Facial driving, including steering the car using head movements.
• Abnormal action detection.
• Lip reading to help command in noisy environments.

Phoenix: The Smart Vehicle

This project involved working with a team to make a level-three self-driving car for Ain Shams University. The system was created for the vehicle to navigate safely on campus to help people with special needs.

I developed a deep reinforcement learning model from the PPO2 algorithm to control the vehicle, which was trained for weeks using multiple agents on the cloud. A single front-facing RGB camera was the only source feeding this model with additional segmentation and feature extraction models to help with scene understanding.

CheckMate

A skilled AI player that I made that can search for millions of moves in seconds with a high probability of winning. I used alpha-beta pruning for tree search, quiescence searches to tackle the horizon effect problem, and the post-thinking algorithm to enhance the search accuracy.

Education

2015 - 2019

Bachelor's Degree in Computer Science

Ain Shams University - Cairo, Egypt

Certifications

JUNE 2023 - PRESENT

Microsoft Certified: Azure AI Engineer Associate

Microsoft

JULY 2018 - PRESENT

Graph Analytics for Big Data

University of California, San Diego | via Coursera

JUNE 2018 - PRESENT

Machine Learning With Big Data

University of California, San Diego | via Coursera

Skills

Libraries/APIs

PyTorch, OpenCV, TensorFlow, Pandas, NumPy, Azure Cognitive Services, Keras, TensorFlow Deep Learning Library (TFLearn), Node.js

Tools

Azure Machine Learning

Languages

Python, Python 3, C++, C

Platforms

Linux, Docker, Azure, Kubernetes

Storage

Azure Cloud Services, Neo4j, Graph Databases

Other

AI Programming, Artificial Intelligence (AI), Convolutional Neural Networks (CNNs), Image Processing, Image Analysis, Image Analytics, Object Detection, Computer Vision, PX4 Autopilot, Research, Machine Learning Operations (MLOps), Team Management, Tesseract, EasyOCR, Robotics, Digital Imaging, Simulations, Deep Learning, Deep Reinforcement Learning, Cloud, Machine Learning, Azure Cognitive Search, Game Theory, Graph Theory, Computer Science, Big Data

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