Mohamed Hazem Labib
About Mohamed Hazem Labib
Mohamed Hazem Labib is a Machine Learning and Software Engineer with four years of experience at Si-Ware Systems and as a self-employed consultant in Egypt. He holds a Bachelor's degree in Electrical and Electronics Engineering from Cairo University and has completed various training programs in marketing, big data, and deep learning.
Work at Si-Ware Systems
Currently, Mohamed Hazem Labib serves as a Machine Learning and Software Engineer at Si-Ware Systems, a position he has held since 2020. He works in Cairo, Egypt, contributing to the development and implementation of machine learning solutions. His role involves utilizing advanced natural language processing (NLP) models to enhance the company's machine learning capabilities.
Self-Employment as Machine Learning Engineer
In addition to his role at Si-Ware Systems, Mohamed Hazem Labib has been self-employed as a Machine Learning Engineer since 2020. He operates from Al Jizah, Egypt, where he applies his expertise in machine learning to various projects. His self-employment allows him to explore diverse applications of machine learning technologies.
Education and Expertise
Mohamed Hazem Labib earned his Bachelor's degree in Electrical and Electronics Engineering from Cairo University, completing his studies from 2015 to 2020. He has furthered his education through various programs, including a Nanodegree in Marketing from Udacity and a Nanodegree in Deep Learning, both completed in 2020. Additionally, he received training in Big Data from IBM in 2019 and studied Business Administration and Management at the American University in Cairo from 2018 to 2019.
Background and Early Experience
Before his current roles, Mohamed Hazem Labib gained practical experience as a trainee at Al Ezz Dekheila Steel Co. EZDK in 2019. This position lasted for one month and took place in Alexandria Governorate, Egypt. His early exposure to the industry has contributed to his understanding of engineering principles and practices.
Technical Skills and Specializations
Mohamed Hazem Labib specializes in both classical machine learning and deep learning techniques. He is experienced in using Trax for building deep learning models and has a strong understanding of convolutional neural networks (CNN) and recurrent neural networks (RNN) architectures. His technical skills enable him to develop robust machine learning solutions tailored to specific applications.