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HuzaifaHanig

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Sindh, Pakistan

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Résumé

Jobs verified_user 0% verified
  • K
    Software Engineer
    Kloudxel
    Mar 2025 - Current (1 year 5 months)
    • Maintained and optimized the RCI Claim Management System built with ASP.NET and React, improving system stability and performance • Enhanced existing features, ensuring a smoother claim processing experience for users.
  • Softech Worldwide
    Associate Backend Engineer
    Softech Worldwide
    Jul 2024 - Feb 2025 (8 months)
    • Designed and implemented messaging systems using Kafka, RabbitMQ, and Azure Bus Service for reliable and scal able event-driven architectures. • Worked with FFmpeg to handle video processing tasks such as encoding, transcoding, and clipping videos,optimizing video workflows for the Vidizmo product. • Successfully migrated their product from Dot net 6 to Dot Net 8 for better performance and security. • Implemented incremental source generators using Roslyn in C# to dynamically generate proxy classes and improve the development process with efficient code generation. • Experienced with dependency injection and design patterns in C# for clean, maintainable, and testable codebase.
  • B
    Management Trainee - Software Developer
    BariTechSol
    Apr 2024 - Jul 2024 (4 months)
    • Contributed to the development and maintenance of a shipping optimization product using ASP.NET Core, React, SQL Server, and a microservices architecture. • Conducted thorough debugging and analysis of the product codebase, successfully identifying and resolving critical issues to improve system stability and performance.
Education verified_user 0% verified
  • National University of Computer and Emerging Sciences
    Bachelors in Computer Science
    National University of Computer and Emerging Sciences
    Aug 2020 - Jun 2024 (3 years 11 months)
Projects (professional or personal) verified_user 0% verified
  • I
    Injuries Detection and Visualization using XAI
    Aug 2023 - May 2024 (10 months)
    Predicting injuries in CT scans forprompt detection of abdominal injuries Python, Pytorch, Tensorflow, Pandas • In trauma settings, prompt detection and localization of injuries are crucial for swift treatment. However, the large number of slices in CT scans often delays the process. This solution is designed to assist medical professionals in efficiently analyzing CT scans. • Predictions of the injuries were done using 2D CNN models such as ImageNet and ResNet and for 3D labels 3D CNN architecture was used. • After prediction of injuries visualizations of those injuries using XAI techniques such as LIME and Grad-CAM.