Mohamed Eltaib
Mohamed Eltaib
Apprenant.e - Il / Lui
(1)
3
Lieu
Toronto, Ontario, Canada
Bio

Computer science major with a background in programming, algorithm design, and data structures. I have a passion for using technology to tackle challenges. I have experience in a variety of programming languages, including Java, Python and C. I also have a large amount of experience in the use of 3D software's and designs.

Portails

Compétences

Application programming interface (api) 1 Fastapi 1 Front end design 1 React.js (javascript library) 1 Sass 1 Unit testing 1 User experience (ux) 1 User interface prototyping 1 User interface (ui) 1 Wordpress 1

Profils sociaux

Réalisations

Dernières rétroactions

Projets récents

Expérience professionnelle

Researcher and Developer
Toronto Metropolitan Aero Design (TMAD)
Toronto, Ontario, Canada
septembre 2024 - Présent

• Implemented computer vision with OpenCV and YOLOv8 for real-time target tracking on moving aircraft
• Integrated vision systems with onboard sensors and Raspberry Pi, ensuring compatibility in dynamic environments
• Tested and calibrated with MATLAB to fine-tune system performance for flight simulations

Software Developer
Ada Analytics
Toronto, Ontario, Canada
janvier 2024 - avril 2024

• Led full-stack development for a finance analytics platform using React.js and Django
• Managed frontend team for code quality and feature development using Git
• Developed APIs with Django REST Framework for processing complex financial data
• Integrated interactive data visualizations with Plotly to enhance user engagement

Éducation

Bachelor of Science, Computer Science
Toronto Metropolitan University
septembre 2022 - Présent

Projets personnels

DryEye AI
https://github.com/burhan-dahod/DryEye

• Developed AI tool predicting droughts by combining historical data with YOLOv8-based drought detection
• Built responsive React frontend and Django backend for seamless data flow
• Used OpenCV to preprocess images, improving drought region identification accuracy
• Generated climate reports to aid farmers and governments in early preparedness

QuickFix
https://github.com/Karishvan/QuickFix

• Built bug tracking system with Flask for real-time team reporting
• Implemented secure user authentication using Scrypt
• Created dashboards with Matplotlib for tracking bug trends and metrics
• Designed scalable SQL database to manage bug and user data