Ahmad I. Elawady

An all-in-one optical character recognition (OCR) software that converts scanned documents, in any language, into fully editable and searchable files.

I was the machine learning researcher responsible for layout extraction and document generation.

Using a mix of deep learning and classical computer vision techniques, I developed a system to extract information such as the lines, the tables, the document's orientation, and the document's background or inpainting.

I also developed a pipelining system that manages how these functionalities are applied. It supports parallel calls to the microservices, handles call dependencies, and dynamically manages the optional calls. I built and deployed a prototype that served these functionalities through RESTful APIs.

A machine learning-based tool to help the chemists with retrosynthesis planning. The project was my end-to-end responsibility. With the support of the SME, I developed tools to filter the chemical reactions, designed and trained ML models, and packaged and deployed the solution to be tested by the client.

At the core of the exercise analysis system, this project captures the motion, identifies the person, detects the actions, and estimates the person's pose. I led the team, designed the system, and deployed it.

A research project aimed at using the YOLOv3 to predict the surrounding vehicles' position and orientation for RGB cameras. It was developed as part of my participation in the Peking University and Baidu's Autonomous Driving competition on Kaggle.

A Python module to embed or facilitate training of the feature extractor. The model is trained to minimize triplet loss. It was developed as a part of my late participation in State Farm's Distracted Driver Detection competition on Kaggle.

A Python module with the tools developed for Kaggle competitions. It includes image processing (e.g., circle centering and a veins highlighter), a pipeline wrapper, and data augmentation. It was developed as a part of my participation in APTOS' 2019 Blindness Detection competition handled on Kaggle.