Mohammed Shehab
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Mohammed Shehab

Mohammed Shehab

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Senior Software Engineer 👨‍💻 | GPUs Developer | Machine Learning Engineer | AI enthusiastic
Montreal, Quebec, Canada

Contact Mohammed regarding: 

work
Full-time jobs
Starting at CAD80K/year ~USD57.3K/year
Flexible work
Starting at CAD45/hour ~USD32.2/hour
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Internships
Starting at CAD2.5K/month ~USD1.79K/month

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Résumé

Jobs verified_user 0% verified
  • C
    Instructor
    Concordia Continuing Education
    Dec 2021 - Current (3 years 6 months)
    Teaching and design courses for undergraduate students and professional education. I am teaching courses: 1- Java and Object Oriented Programming 2- Python Programming 3- Android development for business 4- Practical Machine Learning 5- Operating Systems and Parallel Programming
  • Concordia University
    PhD Candidate
    Concordia University
    Apr 2021 - Current (4 years 2 months)
    Skills: Analytical Skills · Deep Learning · Data Structures · Git
  • Ubisoft
    Machine Learning Engineer
    Ubisoft
    Jul 2018 - Jul 2019 (1 year 1 month)
  • Concordia University
    PhD Student
    Concordia University
    May 2018 - Apr 2021 (3 years)
    Skills: Analytical Skills
  • C
    Software Engineer
    Counterfeit Combat Technology Company
    Mar 2015 - Jan 2018 (2 years 11 months)
    I worked as an Image processing developer to Counterfeit Combat manipulate in the digital image for documents. Furthermore, I was a senior developer for two projects. One of them is a secure document management system (SDMS).
  • J
    Research Associate
    Jordan University of Science And Technology
    Sep 2013 - Apr 2018 (4 years 8 months)
    I am improving many new techniques in data mining, image processing, Machine Learning, and parallel programming. Also, I am a technical developer for other researches by solving programming problems for other researchers and students in the university.
  • D
    Scholarship Holder
    DAAD German Academic Exchange Service
    Sep 2012 - Jun 2015 (2 years 10 months)
  • S
    Software Engineer
    SabafonYemen
    Sep 2010 - Aug 2011 (1 year)
    I was in the technical team support for secondary servers in Aden city. Our responsibility is to maintain and check all UNIX servers.
  • C
    Supervisor of Yemeni students
    Charitable Fund Foundation to support outstanding Yemenis students
    Jul 2009 - Jul 2010 (1 year 1 month)
    I was the supervisor and leader of Yemeni students for a year at Mutah University. The supervisor's responsibility is to monitor, support, and solving students' problems during their study period in Jordan. For instance, students registration in university, finding accommodations for new students, and organizing all student's activities. Also, I was managing the financial supports from the organizations and the Embassy of Yemen in Riyadh (Saudi Arabia) and Amman (Jordan). This financial support including salaries, university tuitions, and awards.
Education verified_user 0% verified
  • Concordia University
    Doctor of Philosophy - PhD, Electrical and Computer Engineering
    Concordia University
    Jan 2018 - Current (7 years 5 months)
    Skills: Deep Learning · Git · Data Structures
  • J
    Master’s Degree, Computer Science
    Jordan University of Science And Technology
    Sep 2012 - Jun 2015 (2 years 10 months)
    I improved image processing algorithms' performance- especially on image segmentation processing- by using Graphics Processing Unit Capabilities for Medical Images (Brain tumor and Breast Cancer). The code implementation was done using the CUDA programming language. I published more than four papers from my thesis and more than 30 researches in Natural Language Processing, Bioinformatics, and High-Performance Computing.
  • M
    Bachelor's Degree, Computer Science
    Mutah University
    Sep 2006 - May 2010 (3 years 9 months)
    I designed a web for delivery system EX: (DHL Company) website and mobile application with C# language. Completed this project a half week ahead of schedule and achieved 96 grades.
Projects verified_user 0% verified
  • G
    Grover's Algorithm Implementation and Visualization
    Sep 2023 - Dec 2023 (4 months)
    Skills: Quantum Computing · Java · Parallel Programming
  • E
    E-Health System and Consulting
    Jan 2018 - Current (7 years 5 months)
    The project was conceptualized, developed, and launched for commercial use, catering to diverse platforms such as websites and smartphones (Android and IOS). The system comprises five key components: 1) Search Engine 2) Recommendation System 3) Payment System 4) Direct Chat Interface for Customers and Nutrition Specialists 5) Advertising and E-commerce Environments My role involved the comprehensive implementation of a full-stack website, which included creating RestFul APIs for smartphones. Additionally, I handled the deployment process on the Azure portal to ensure seamless operation.
Awards verified_user 0% verified
  • C
    CIFAR Deep Learning + Reinforcement Learning Summer School
    CIFAR
    Aug 2021
    Every year, the CIFAR Deep Learning + Reinforcement Learning (DLRL) Summer School brings together graduate students, post-docs and professionals to cover the foundational research, new developments, and real-world applications of deep learning and reinforcement learning.
  • Concordia University
    Concordia International Tuition Award of Excellence
    Concordia University
    May 2018
Publications verified_user 0% verified
  • Elsevier
    Commit-time defect prediction using one-class classification
    Elsevier
    Nov 2023
    Existing Just-In-Time Software Defect Prediction methods suffer from the data imbalance problem, where the majority class (normal commits) significantly outnumbers the minority class (buggy commits). This results in a higher probability of misclassification. Various data balancing techniques have been proposed to address this challenge with varying degrees of success. In this study, we propose an approach that rely on One-Class Classification (OCC) to train models using data from the majority class only. This eliminates the need for data balancing. We compare the accuracy of three OCC algorithms - One-class SVM, Isolation Forest, and One-class k-NN - to their binary counterparts - SVM, Random Forest, and k-NN - on 34 software projects. Our
  • IEEE
    JITBoost: Boosting Just-In-Time Defect Prediction Using Boolean Combination of Classifiers
    IEEE
    Oct 2023
    Just-In-Time Software Defects Prediction (JIT-SDP) plays a critical role in software engineering by enabling the early identification of potential defects before they impact system performance. This study investigates the effectiveness of Boolean Combination of Classifiers (BCC) in building effective JIT-SDP models. We propose the JITBoost framework, which leverages three BCC algorithms, namely Brute-force Boolean Combination (BBC), Iterative Boolean Combination (IBC), and Weighted Pruning Iterative Boolean Combination (WPIBC). JITBoost combines the decisions of six traditional machine learning algorithms and one deep learning algorithm. When applied to 259K commits of 34 projects, we show that JITBoost models perform better than traditiona